Guillaume Andre Durand

Didier Raoult

Gregory Dubourg
email: greg.dubourg@gmail.com

Guillaume André Durand

Grégory Dubourg

Dr Grégory Dubourg

Mephi

Guillaume André Durand

Grégory Dubourg

Dr Grégory Dubourg

Antibiotic discovery: history, methods and perspectives

Keywords: Antibacterial Agents, drug resistance, Actinobacteria, gastrointestinal microbiome, gut Units, coloration, or optical density measurement Indicator strain Tested strain Antibiotic discovery: history, methods and perspectives Antibacterial Agents, drug resistance, Actinobacteria, gastrointestinal microbiome, gut

Introduction

Antibiotic resistance is considered a major public health concern by several international organizations and by local agencies [1][2][3]. As a matter of fact, the Centers for Disease Control and Prevention claim 23,000 deaths each year in the US related to antibiotic resistance and some studies predict millions of deaths in the coming decades [4][5][6]. The United Nations then created a group in order to coordinate the fight against antibiotic resistance [7]. Interestingly, the global mortality related to infectious diseases is decreasing every year, from 10,7 million deaths in 2005 to 8,6 million in 2015 [8]. In addition, it was recently shown that the current mortality due to antibiotic resistance seems far from these predictions [9]. One of the approaches used over the past decade to treat Multi-Drug Resistant (MDR) and Extremely-Drug Resistant (XDR) bacteria was to break the vicious circle of Betalactams, enlarging the panel of antimicrobial agents commonly tested. It has been demonstrated that "old" antibiotics (i.e. forgotten molecules) had remarkable efficacy against such isolates. For instance, minocycline, sulfadiazine and clofazimine are active against XDR tuberculosis strains, as for fosfomycin, colistin and minocycline against multi-drug resistant Gram-negative isolates [10,11].

According to the World Health Organization, antimicrobial resistance control policies include the rational use of antibiotics, in particular on farms, the increase of surveillance, and the research and development for new tools and molecules [12]. Indeed, despite the rising number of available molecules (Figure 1), the last new class of antibiotic discovered is daptomycin (1986), which was only approved in 2003 by the Food and Drug Administration (FDA) [13][14][15]. This fact confirms that antimicrobial agents found on the market in the last 30 years are associations or improvements of existing molecules. Examples are given of new antibiotics recently marketed that belong to an already known class, such as oxazolidinones (tedizolide), lipoglycopeptides (dalbavancin), or cephalosporins (ceftaroline, ceftobiprole).

Combination of improved molecules of an already known class is another example of recently commercialized new antibiotics, as for example ceftolozane plus tazobactam, or ceftazidime plus avibactam. The research and development of a totally new class of antibiotic appear as a major issue. Herein, we propose to recall the history of antibiotic discovery, their structural nature, and the methods that were used for their discovery. Finally, we review the potential new approaches for the discovery of new classes of antibiotics.

The history of antibiotics

Antibiotic resistance is in fact very ancient

Most of the antibiotics currently used in human medicine are natural secretions of environmental bacteria or fungi. Indeed, the majority of antibiotics currently used are derived from Streptomyces isolated from soil samples [16]. In their natural environment, microorganisms have to fight against each other by producing antimicrobial substances, and have to develop resistance mechanisms to other antimicrobials [17]. Secondly, the species naturally producing antibacterials also have resistance genes to these antibacterials in order to avoid self-toxicity, within a biosynthetic antibiotic operon [18]. D 'Costa et al. demonstrated the presence of antibacterial resistance genes in an environment in which there was no innate antibiotic. They first proposed the existence of a "reservoir of resistance determinants that can be mobilized into the microbial community" [19]. Gerard D. Wright proposed the term "resistome" to design the collection of all the antibiotic resistance genes and their precursors in bacteria [20].

Interestingly, multi-drug resistant bacterial species as well as resistance genes to antibiotics currently used were also found from environmental archaeological samples. The OXA genes that encode beta-lactamases have been dated to several million years [21]. D'Costa et al. have found resistance genes to β-lactam, tetracyclines and glycopeptides from 30,000 years old permafrost samples [22]. Kashuba et al. have found several resistance genes in the genome of a Staphylococcus hominis isolated from permafrost [23]. Of the 93 strains cultured by Bhullar et al. from the 4 million-year-old Lechuguilla cave (New Mexico), 65% of the species were resistant in vitro to three or four antibiotics classes [24]. Also, resistance genes to β-lactam and glycopeptides were also found in the 5,300-year-old gut microbiome of the mummy Ötzi [25]. Recently, 177 antibiotic resistance genes belonging to 23 families (that represent all the mechanisms of resistance, i.e. mutation, efflux and antibiotic inactivation) were found in the antibiotic naïve Mackay Glacier region [26].

Orthologous genes within mobile elements known from environmental bacteria were also found in bacteria isolated from clinical isolates [19]. For instance, Marshall et al. found orthologous genes of the van HAX cassette from the environmental species Streptomyces toyocaensis and Amycolatopsis orientalis [27]. This cassette is responsible for the glycopeptide resistance of Enterococcus faecium. Some experimental studies seem to show that transfer of resistance genes from environmental producers in the soil to human pathogenic species is possible [28]. The horizontal gene transfer of entire clusters of resistance genes from the resistome to clinical strains under selective pressure related to the human use of antibiotics is actually suspected [29].

Historic of the antibiotic discovery

Antibiotics were used for a long time before the advent of modern medicine. The effects of bread on which filamentous fungi grew for the treatment of wounds and burns has been known since ancient Egypt [30]. In the Middle Ages, healers in China and Greece used musty textures to treat various ailments. In the 19 th century, Sir John Scott Burden-Sanderson noticed the absence of bacteria from a liquid growth culture covered with mould. In 1871, Joseph Lister discovered the inhibitory effects of Penicillium glaucum on bacterial growth, allowing him to cure a nurse's injury with Penicillium glaucum extracts. At the same time, Louis Pasteur noticed that some bacteria could inhibit others. He discovered with his colleague Jules François Joubert in 1877, while studying the growth of Bacillus anthracis in urine samples, that it was inhibited when co-cultivated with "common" aerobic bacteria. In In 1928, Alexander Fleming accidentally discovered in his forgotten colonies of Staphylococcus aureus that a fungus was inhibiting the growth of Staphylococcus. The Penicillium notatum molecule has been purified and called penicillin. But the industrial production of this antibiotic was performed only in 1940 by Howard Florey et Ernst Chain, using Penicillium chrysogenum [33]. Fleming also discovered the lysozyme, an antibacterial enzyme [33]. In 1930, René Dubos discovered an enzyme from a soil-derived Bacillus that specifically decomposes Streptococcus pneumoniae type III capsular polysaccharide. With this enzyme, he was able to treat mice with pneumococcal peritonitis [34]. Ten years later, he isolated from Bacillus brevis the oligopeptide gramicidin that widely inhibited Gram-positive species [35]. Unfortunately, gramicidin showed too much toxicity for humans, except for local treatment [36]. In the US, Selman Waksman was the first to perform a systematic research of antimicrobial activity of soil bacteria, particularly from Streptomyces members or Streptomycetes. He developed several culture techniques and strategies ("Waksman platform") in order to highlight antagonisms between bacterial species [37]. Using his platform, he discovered in the 40's several major antibiotics and antifungals, such as actinomycin (from Streptomyces spp.) [38], streptomycin (from Streptomyces griseus) [39], neomycin (from Streptomyces fradiae) [40], fumigacin (from Aspergillus fumigatus) and clavacin (from Aspergillus clavatus) [41]. Actinomycin, neomycin and streptomycin are still in use today. Moreover, streptomycin has revolutionized the treatment of tuberculosis, and is still active against multi-drug resistant tuberculosis [42]. The pharmaceutical industry was inspired by the Waksman platform, which led to the discovery of all current antibiotics between the 1940s and the 1970s. During this golden age, 23 classes of antibiotic were discovered from 19 bacterial species and 7 fungi (Table 1).

Despite recent commercialization for some, the last classes of antibiotic discovered are from the 1980s. After 50 years of discoveries, no new classes have been found. Therefore, new strategies were needed. After the culture approach through Waksman's platform, the industry turned to the in vitro synthetization of new molecules, based on knowledge of the known mechanism of action of antibiotics. Unfortunately, few new classes of antibiotics have been discovered, the nitrofuran in 1953, the quinolone in 1960, the sulphonamide in 1961 and oxazolidinones in 1987. The modification and improvement of already known molecules has also been carried out. This is reflected by the commercialization of linezolid in 2003 and daptomycin in 2001, although these molecules had been known since 1955 and 1986, respectively [32]. Recently, a new cephalosporin called cefiderocol was found to be active against carbapenem-resistant Gram-negative bacteria [43]. Hemisynthetic compounds from natural products were also developed, such as ketolides (derived from macrolides) or metronidazole (derived from a natural product of Streptomyces sp.) (Table 1). But the lack of return on investment and the emergence of resistance have led the industry to gradually let down the research on antibiotics, preferring to invest in drugs for chronic diseases [32]. Of the 20 pharmaceutical companies that invested in antibiotic discovery in the 1980s, there were only five left by 2015. [44]. More than 1,200 antimicrobial peptides were discovered from various origins, from plants to invertebrates and animals, but none has been used as an antibiotic [45]. In conclusion, the majority of antibiotics were discovered during the golden age. Bacteria and fungi were the greatest producers. The genus Streptomyces is the source of about half of the antimicrobial agents currently used in human medicine (Table 1).

Chemical nature of antimicrobial agents

Antimicrobial molecules are represented by a wide variety of chemical compounds.

Most of the time, they are natural products and secondary metabolites, implying that they are not required for survival under laboratory conditions but still provide some advantages in the environment [46]. Among the antimicrobial substances used in human medicine, it is possible to classify antibiotics in five groups of chemical molecules. The first are derived amino acids that are non-ribosomally synthesized (non-ribosomally synthetized peptides, NRP). The second are acetyl coenzyme A or malonyl coenzyme A derived (polyketides, PK). NRP and PK represent about 50% of all current antibiotics (Table 1). The third are hybrids between NRP and PK and the fourth are composed of several carbohydrates units substituted with amine groups (aminoglycosides). And finally, the last group is composed of various molecules, such as terpenoids, fusidic acid or alkaloids such as metronidazole. In addition to these molecules used as antibiotics, thousands of antimicrobial peptides are known from insects, mammals, plants or amphibians [47]. These peptides are usually classified as "ribosomally synthesized and post-translationally modified peptides" (RiPPs), a subgroup of natural products [48].

Antibiotics

The NRP and PK are synthetized by multi-enzymatic complexes (non-ribosomal peptides synthetase, NRPS and polyketides synthetase, PKS) encoded by biosynthetic gene clusters [49]. These complexes are organized in modules including several domains. For example, the erythromycin synthase complex consists of three proteins and seven modules each containing three to six domains. [49]. The NRPS use amino acids as substrate elongated by peptidic connection, whereas PKS use acyl-coenzyme A as substrate elongated by Claisen condensation reaction [49]. This complex organization allows the production of a great number of different products, and therefore a great diversity. For example, ciclosporin belongs to the NRP category [50]. Hybrid assembly line that uses both amino acids and acetyl coenzyme A, or fatty acid synthetases (FAS), are also described [51]. NRP antibiotics comprise molecules such as β-lactams, daptomycin, lincomycin, polymyxins, and vancomycin while macrolides, mupirocin and tetracyclines belong to polyketides antibiotics.

Rifampicin belongs to hybrid NRP/PK (Table 1).

Antimicrobial peptides

Antimicrobial peptides are broad spectrum antibacterial molecules that have been discovered in blood cells in 1957 by Robert Skarnes [52]. They belong to natural products that are small peptides (i.e. less than 100 amino acids) ribosomally synthesized with posttranslational modifications (RiPPs). Natural peptides have a multifunctional activity that participates in innate immunity in eukaryotic and prokaryotic cells. [47]. Antimicrobial peptides are evolutionary well-conserved amphipathic molecules with hydrophobic and cationic amino-acids [53]. They can be categorized according to their secondary conformation: group I (alpha helical), group II (beta sheet), group III (mixed) and IV (extended) [54]. They have been isolated from almost all living organisms from prokaryotes to vertebrates. Indeed, thousands of antimicrobial peptides are known and come from insects, plants, or amphibians [45,47]. The main known mechanisms of action are related to their cationic charge and amphipathic structure, responsible for the membrane disruption of the negatively charged bacterial cell. Antimicrobial peptides can also interact with membraneassociated protein targets, as well as intracellular targets after penetration into the bacterial cytoplasm [54]. Finally, antimicrobial peptides can also have immunomodulatory effects on the innate immune system of the host [55].

Bacteriocins are antimicrobial peptides that were first discovered in bacterial species.

They are used in the agro-alimentary industry as food preservatives and in veterinary medicine [56]. Bacteriocins are separated into four groups: class I are small heat-stable posttranslationally modified peptides (<5kDa) which use the amino acid lanthionine, there are therefore called lantibiotics; class II are not modified heat-stable small peptides (<10kDa) which do not use lanthionine; class III are large heat-labile peptides (>30kDa) and class IV are complex or cyclic peptides containing lipids or carbohydrates [56]. Bacteriocins inhibited closely related species [57]. For example, lacticin 3147 and nisin are lantibiotics that exhibited an antibiotic activity against Gram-positive bacteria, notably Meticillin-resistant Staphylococcus aureus (MRSA) or Vancomycin-resistant Enterococcus [58]. Nisin is the most famous lantibiotic, largely used as food preservative because of its activity against Listeria monocytogenes, MRSA and Streptococcus pneumoniae [59]. Nisin is also used in veterinary medicine under the name Wipe Out ® for the prevention of dairy mastitis [57]. The synergistic effects of lantibiotics with antibiotics have also been demonstrated in vitro [60].

According to the Antimicrobial Peptide database, 2,478 antibacterial peptides are already known [61]. All medical fields combined, 60 peptides have obtained the FDA approval and 140 are in clinical trials, mainly for oncological and metabolic diseases [62].

Yet, when focusing on infectious diseases, only 12 naturally occurring antimicrobial peptides have reached the stage of human clinical trial. (Table 2). Among them, only three (LYX-109, LL-37 and nisin) demonstrated a better efficacy than placebo, but none obtained the FDA approval for human application. Only gramicidin has received FDA approval for topical application in association with polymyxin and neomycin for ophthalmic use. Teixobactin is a new promising depsipeptide that provides an inhibition of S. aureus and M. tuberculosis [63].

This molecule uses notably the rare amino acid L-allo-enduracididine, which is challenging to synthesize and therefore limits its use despite efforts made to develop analogues [64]. Despite their narrow or broad spectrum of activity against human pathogens and easier bioengineering compared to NRPS or PKS, bacteriocins are not used in humans as antibiotics due to several limitations.

The main limitations in the use of antimicrobial peptides as antibiotics in clinical practice are their instability (proteolytic digestion, oxidation), their high cost and low yield of production, their short half-life, and their quick elimination [60]. Notably, their low bioavailability after oral ingestion related to proteolytic degradation is a great bottleneck. To solve these problems, production of analogues using rational drug design or nano-engineering is used to improve the pharmacokinetic properties. For instance, nano-engineering has increased the nisin spectrum to Gram-negative bacterial species [65] or allowed HPA3P HIS to be highly effective against Vibrio vulnificus in a mouse model [66]. The use of nanoparticles also prolonged the stay in the stomach of pexiganan after oral administration, which reduces the concentration of pexiganan required in a mouse model for Helicobacter pylori eradication [67]. Another approach is the combination of bacteriocins with other antimicrobials in order to reduce the resistance risk and to increase the antimicrobial potency [60]. Another matter of concern with AMP is the risk of development of resistance against our own immunity peptides. For instance, pexiganan have been previously found to induce cross-resistance to human-neutrophil-defensine 1 [68].

Methods for the discovery of antibiotics

Culture-based approaches

In the 1940s, Selman Waksman systematically screened the soil bacteria for antagonisms. Its culture-based approach is still in use today [69]. All the methods are based on the same principle: showing an inhibition of a tested strain over an indicator strain closely cultivated. The tested strain is the strain suspected to produce antimicrobials targeting the strain used as indicator. Several techniques exist to detect antimicrobial activity, either in solid or in liquid culture. There are three main methods regarding solid culture approaches: the cross-streak method, the spot-on-the-lawn and the well diffusion method (Figure 2).

The cross streak is the inoculation of the bacterial strain tested vertically on the agar plate. The incubation time of the plate depends on the life cycle of the bacterial strain required to reach the exponential phase, which is the moment where secondary metabolites are excreted. Then, the indicator strain is inoculated into horizontal streaks and the plate is incubated (Figure 2) [70]. This technique is easy and powerful for screening but requires that both bacterial strains have the same culture conditions (e.g., atmosphere, temperature and growth duration).

The second and the third methods are respectively called "spot-on-the-lawn" and "well diffusion method". The "spot-on-the-lawn" method consists in depositing a drop of the tested strain on a lawn of the indicator strain [71]. After incubation, an inhibition zone is searched around the sediment. The "well diffusion method" is based on the diffusion of antimicrobials through agar which inhibits sensitive species. An agar plate is pooled with the indicator strain or inoculated with a lawn of the indicator and agar holes are punched out aseptically. Then, two main variants exist. The first is the Agar Plug Diffusion method which consists in removing a cylinder of agar from a plate previously inoculated with the tested strain. This cylinder of agar is then placed into the hole of the indicator plate [72]. The second variant method consists in placing a liquid broth of the tested strain or a growth supernatant in the hole [73]. After an optional rest time at +4°C, the agar plate is incubated and inhibition growth zones are measured (Figure 2). Several variants were developed, like using stress conditions or iron chelator [74,75]. The main limitation of solid culture tests concerns bacterial species that have different growth conditions or fastidious species.

Liquid culture-based approaches can solve this problem. Liquid broth co-culture has been used since the existence of the Waksman platform [69]. This is the simultaneous culture of the tested species and the indicator strain separated by a filter allowing the diffusion of nutrients but not the diffusion of cells. Following incubation, the bacterial growth of the indicator strain is determined by numeration, coloration or optical density [69]. Another method is to add the growth supernatant of the test species previously filtered and concentrated to a liquid culture of the indicator strain [76]. The latter method allows the bacteria tested to be grown under conditions different from those of the indicator strain (Figure 3).

Discovering antimicrobial effects from already known compounds

Some antibiotics were discovered years before they were used (fidaxomycine, daptomycin, or linezolid). Several million of chemical compounds are known in chemical databases and could provide a potential source of antibiotics [32]. Moy et al. have tested the activity against E. faecalis of more than 6,000 chemical compounds and 1,136 natural products in the Caenorhabditis elegans animal model, discovering 16 molecules increasing the survival of animals [77]. The bottleneck remains the selection and the high throughput testing of these molecules.

Synthesis of new molecules and improvement of already known compounds

The « Rational Drug Design » consists in the empirical synthesis of new molecules that are designed according to several rules to be well-absorbed, non-toxic, and active against a specific target [32]. The most famous rules used by the industry are Lipinsks's rules.

Despite more than 10 million of new molecules synthesized, only a few active molecules have reached the market, notably antituberculous drugs [32,37] (Table 1). This can be explained by the fact that antibiotics have generally poor economics [78].

The improvement of already known molecules is another strategy that can yield benefits. The modification of cephalosporin lead to the development of cefiderocol, that demonstrated safety and tolerability in healthy subjects, and clinical trials for the treatment of urinary tract infections are ongoing [79]. Another example is the modification of the aminoglycoside sisomicin that leads to the development of plazomicin [80]. This antibiotic was recently approved by the FDA and a small phase 2 clinical trial found it had an efficacy comparable to that of levofloxacin in the treatment of urinary tract infections and acute pyelonephritis [81]. If the potential use of these antibiotics remains to determine, their mechanism of action is not novel, and the apparition of resistance is expected in the same way as for their related antibiotic parent.

4.4.Genome mining

Secondary metabolites are encoded by Biosynthetic Gene Cluster (BGCs). Thousands of prokaryotic genomes are available in sequence databases. These data have generated thousands of BGCs that potentially encode unknown molecules [82,83]. Despite the fact that many of them do not have any antimicrobial activity, little is known about them. Walsh et al. [83,85]. For instance, lichenicidin is a bacteriocin synthesized by Bacillus licheniformis that was discovered using the mode-of-action genome mining approach. The authors screened the databases for LanM genes, which are involved in the biosynthesis of lantibiotics [86]. The identification of putative bacteriocins encoded by BGC from the genome sequence is possible using bioinformatic algorithms [87]. Bacteriocins are easily found using bioinformatic tools compared to NRPS or PKS. Tools such as BAGEL, antiSMASH or PRISM are widely used for this purpose. These tools exploit two main approaches [83]. The first consists in finding new congeners of already known scaffolds. This approach is based on the homology comparison by the research of conserved domains (anchors), as for the thiotemplate domain of NRPS and PKS [88]. Small structural changes of the new homologue may result in a significant change in the activity of the product. The second approach is more difficult and consists in finding new scaffolds. Predicting the chemical structure and biological activity of a BGC informatic sequence is a real challenge [83]. The main problem that remains is proving the functional activity of BGC [89]. Both approaches often require the engineering expression of BGC from the native host or from a heterologous host, which represents the main bottleneck of genome mining for the discovery of new antibiotics.

Recently, Hover et al. have screened more than 2,000 soil samples from various areas of the US, searching for BGCs encoding calcium-binding motif Asp-X-Asp-Gly [90]. This motif is related to calcium-dependant antibiotics such as lipopeptides, for which the mechanism of action is not fully understood [91]. They found several clades of uncharacterized BGC, of which the most abundant was present in 19% of all samples. This clade was named malacidins, the molecules were then synthesised, and their antibiotic activity was characterized in vitro. The malacidin A exhibited a broadly antibiotic activity against Gram-positive bacteria, notably MRSA, which was successfully confirmed in a skin-wound infection rat model. In conclusion, genome mining is a promising approach for new antibiotic discovery, despite the fact that the method is fastidious and time-consuming.

4.5.CRISPR Cas9

Bacteria and fungi have an immune system that protects them from foreign genetic material that could be inserted by phages. This immune system consists of restriction enzymes, toxin-antitoxin and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) Cas system [92]. The utilization of CRISPR Cas9 to design new antimicrobials with a predetermined activity spectrum has been already performed with promising results.

Citorik et al. have developed RNA-guided nucleases that target the resistance gene bla SHV-18 and bla NDM-1 . After transformation by plasmids and transduction by bacteriophages, the authors observed a significant reduction in the number of E. coli containing the targeted resistance gene, either chromosomal or plasmid [93]. The same approach has been successfully tested using phagemid targeting the S. aureus methicillin resistance gene [94].

The same authors tested the use of bacteriophages in a mouse model of S. aureus skin infection with an efficacy comparable to that of mupirocin [94]. Other authors used genome editing technology to re-sensitize MDR cells. As an example, Kim et al. used CRISPR Cas9 to target a conserved sequence of Extended-Spectrum β-Lactamases, thus restoring the susceptibility of E.coli in their in vitro model [95].

Conclusion and perspective

More than three quarters of all antibiotics currently used in human health are natural products or derived from them. The discovery of antibiotics declined after the 1970s due to the difficulty of cultivating bacterial species from soil under laboratory conditions. New innovative culture approaches were then created thanks to the bloom of new molecular methods. In this way, genome mining searching for new BGCs as well as CRISPR Cas9 technology are promising new approaches. Recently, the ability to rapidly identify bacterial strains using Matrix Assisted Laser Desorption Ionisation Time of Flight (MALDI Tof) has permitted the rebirth of culture. Therefore, new culture approaches trying to mimic the natural environment were invented in order to grow fastidious species. This led to the discovery of new bacterial species. For instance, Ling et al. discovered the new antibiotic teixobactin from the new species Eleftheria terrae isolated in the soil using a diffusion chamber [63].

The same approach is now possible for the human-associated microbiota. The nose is an example of ecological niche poor in nutrients in which the microbiota is probably in strong competition [75]. Using a home-made nasal synthetic medium under iron-limited condition, Krismer B et al. discovered lugdunin, a new antibiotic inhibiting S. aureus growth [74]. The gut microbiota is another microbiota of interest for antibiotic research. Indeed, the human gut has an average load concentration ranging from 10 4 to 10 12 CFU/mL from the duodenum to the colon. These species live in extreme competition, as they did before human colonization where bacteria lived in a competitive world that led them to naturally develop many antimicrobial products. Metagenomic analysis from the human gut microbiota found many BGCs. In 2014, Donia et al. found 3,118 BGCs including NRPS, RiPPs and PKs in the human microbiome. They also found 599 BGCs in the gut. Taken together with the oral cavity, it is one of the richest sites in BGCs of the human microbiota. They also found and purified lactocillin, a new thiopeptide antibiotic, isolated from the vaginal microbiota [96].

The study of the gut microbiota using culture methods was recently improved by culturomics, a novel approach that consists in the multiplication of growth conditions [97].

This has led to the discovery of previously uncultivated species. With this approach, Lagier et al. significantly increased in a couple of years the gut repertoire from 690 to 1,525 species, of which 247 were totally new [98]. Indeed, the new species described from the gut represent an opportunity for the research for novel antibiotics. The search for new antibiotics naturally synthesized by organisms living in complex ecosystems like the gut microbiota, using the culture approach, seems the modern continuity of what has already worked in the past. Thus, if the study of antagonisms between environmental bacteria has led to the discovery of a substantial proportion of antibiotic classes, such studies were rarely performed from humanderived microbiota.

In conclusion, the research for new antibiotic molecules is a key point among the strategies for the fight against antibiotic resistance. The recent advances from both culturedependant and culture-independent methods of exploration of complex ecosystems such as soil or human-associated microbiota open a new era in antimicrobial research.

Introduction

Antibiotic resistance is considered a major public health concern by several international organizations and by local agencies [1][2][3]. As a matter of fact, the Centers for Disease Control and Prevention claim 23,000 deaths each year in the US related to antibiotic resistance and some studies predict millions of deaths in the coming decades [4][5][6]. The United Nations then created a group in order to coordinate the fight against antibiotic resistance [7]. Interestingly, the global mortality related to infectious diseases is decreasing every year, from 10,7 million deaths in 2005 to 8,6 million in 2015 [8]. In addition, it was recently shown that the current mortality due to antibiotic resistance seems far from these predictions [9]. One of the approaches used over the past decade to treat Multi-Drug Resistant (MDR) and Extremely-Drug Resistant (XDR) bacteria was to break the vicious circle of Betalactams, enlarging the panel of antimicrobial agents commonly tested. It has been demonstrated that "old" antibiotics (i.e. forgotten molecules) had remarkable efficacy against such isolates. For instance, minocycline, sulfadiazine and clofazimine are active against XDR tuberculosis strains, as for fosfomycin, colistin and minocycline against multi-drug resistant Gram-negative isolates [10,11].

According to the World Health Organization, antimicrobial resistance control policies include the rational use of antibiotics, in particular on farms, the increase of surveillance, and the research and development for new tools and molecules [12]. Indeed, despite the rising number of available molecules (Figure 1), the last new class of antibiotic discovered is daptomycin (1986), which was only approved in 2003 by the Food and Drug Administration (FDA) [13][14][15]. This fact confirms that antimicrobial agents found on the market in the last 30 years are associations or improvements of existing molecules. Examples are given of new antibiotics recently marketed that belong to an already known class, such as oxazolidinones (tedizolide), lipoglycopeptides (dalbavancin), or cephalosporins (ceftaroline, ceftobiprole).

Combination of improved molecules of an already known class is another example of recently commercialized new antibiotics, as for example ceftolozane plus tazobactam, or ceftazidime plus avibactam. The research and development of a totally new class of antibiotic appear as a major issue. Herein, we propose to recall the history of antibiotic discovery, their structural nature, and the methods that were used for their discovery. Finally, we review the potential new approaches for the discovery of new classes of antibiotics.

The history of antibiotics

Antibiotic resistance is in fact very ancient

Most of the antibiotics currently used in human medicine are natural secretions of environmental bacteria or fungi. Indeed, the majority of antibiotics currently used are derived from Streptomyces isolated from soil samples [16]. In their natural environment, microorganisms have to fight against each other by producing antimicrobial substances, and have to develop resistance mechanisms to other antimicrobials [17]. Secondly, the species naturally producing antibacterials also have resistance genes to these antibacterials in order to avoid self-toxicity, within a biosynthetic antibiotic operon [18]. D'Costa et al. demonstrated the presence of antibacterial resistance genes in an environment in which there was no innate antibiotic. They first proposed the existence of a "reservoir of resistance determinants that can be mobilized into the microbial community" [19]. Gerard D. Wright proposed the term "resistome" to design the collection of all the antibiotic resistance genes and their precursors in bacteria [20].

Interestingly, multi-drug resistant bacterial species as well as resistance genes to antibiotics currently used were also found from environmental archaeological samples. The OXA genes that encode beta-lactamases have been dated to several million years [21]. of the species were resistant in vitro to three or four antibiotics classes [24]. Also, resistance genes to β-lactam and glycopeptides were also found in the 5,300-year-old gut microbiome of the mummy Ötzi [25]. Recently, 177 antibiotic resistance genes belonging to 23 families (that represent all the mechanisms of resistance, i.e. mutation, efflux and antibiotic inactivation)

D
were found in the antibiotic naïve Mackay Glacier region [26].

Orthologous genes within mobile elements known from environmental bacteria were also found in bacteria isolated from clinical isolates [19]. For instance, Marshall et al. found orthologous genes of the van HAX cassette from the environmental species Streptomyces toyocaensis and Amycolatopsis orientalis [27]. This cassette is responsible for the glycopeptide resistance of Enterococcus faecium. Some experimental studies seem to show that transfer of resistance genes from environmental producers in the soil to human pathogenic species is possible [28]. The horizontal gene transfer of entire clusters of resistance genes from the resistome to clinical strains under selective pressure related to the human use of antibiotics is actually suspected [29].

Historic of the antibiotic discovery

Antibiotics were used for a long time before the advent of modern medicine. The effects of bread on which filamentous fungi grew for the treatment of wounds and burns has been known since ancient Egypt [30]. In the Middle Ages, healers in China and Greece used musty textures to treat various ailments. In the 19 th century, Sir John Scott Burden-Sanderson noticed the absence of bacteria from a liquid growth culture covered with mould. In 1871, Joseph Lister discovered the inhibitory effects of Penicillium glaucum on bacterial growth, allowing him to cure a nurse's injury with Penicillium glaucum extracts. At the same time, Louis Pasteur noticed that some bacteria could inhibit others. He discovered with his colleague Jules François Joubert in 1877, while studying the growth of Bacillus anthracis in urine samples, that it was inhibited when co-cultivated with "common" aerobic bacteria. In using Penicillium chrysogenum [33]. Fleming also discovered the lysozyme, an antibacterial enzyme [33]. In 1930, René Dubos discovered an enzyme from a soil-derived Bacillus that specifically decomposes Streptococcus pneumoniae type III capsular polysaccharide. With this enzyme, he was able to treat mice with pneumococcal peritonitis [34]. Ten years later, he isolated from Bacillus brevis the oligopeptide gramicidin that widely inhibited Gram-positive species [35]. Unfortunately, gramicidin showed too much toxicity for humans, except for local treatment [36]. In the US, Selman Waksman was the first to perform a systematic research of antimicrobial activity of soil bacteria, particularly from Streptomyces members or Streptomycetes. He developed several culture techniques and strategies ("Waksman platform") in order to highlight antagonisms between bacterial species [37]. Using his platform, he discovered in the 40's several major antibiotics and antifungals, such as actinomycin (from Streptomyces spp.) [38], streptomycin (from Streptomyces griseus) [39],

neomycin (from Streptomyces fradiae) [40], fumigacin (from Aspergillus fumigatus) and clavacin (from Aspergillus clavatus) [41]. Actinomycin, neomycin and streptomycin are still in use today. Moreover, streptomycin has revolutionized the treatment of tuberculosis, and is still active against multi-drug resistant tuberculosis [42]. The pharmaceutical industry was inspired by the Waksman platform, which led to the discovery of all current antibiotics between the 1940s and the 1970s. During this golden age, 23 classes of antibiotic were discovered from 19 bacterial species and 7 fungi (Table 1).

Despite recent commercialization for some, the last classes of antibiotic discovered are from the 1980s. After 50 years of discoveries, no new classes have been found. Therefore, new strategies were needed. After the culture approach through Waksman's platform, the respectively [32]. Recently, a new cephalosporin called cefiderocol was found to be active against carbapenem-resistant Gram-negative bacteria [43]. Hemisynthetic compounds from natural products were also developed, such as ketolides (derived from macrolides) or metronidazole (derived from a natural product of Streptomyces sp.) (Table 1). But the lack of return on investment and the emergence of resistance have led the industry to gradually let down the research on antibiotics, preferring to invest in drugs for chronic diseases [32]. Of the 20 pharmaceutical companies that invested in antibiotic discovery in the 1980s, there were only five left by 2015. [44]. More than 1,200 antimicrobial peptides were discovered from various origins, from plants to invertebrates and animals, but none has been used as an antibiotic [45]. In conclusion, the majority of antibiotics were discovered during the golden age. Bacteria and fungi were the greatest producers. The genus Streptomyces is the source of about half of the antimicrobial agents currently used in human medicine (Table 1).

Chemical nature of antimicrobial agents

Antimicrobial molecules are represented by a wide variety of chemical compounds.

Most of the time, they are natural products and secondary metabolites, implying that they are not required for survival under laboratory conditions but still provide some advantages in the environment [46]. Among the antimicrobial substances used in human medicine, it is possible to classify antibiotics in five groups of chemical molecules. The first are derived amino acids that are non-ribosomally synthesized (non-ribosomally synthetized peptides, NRP). The second are acetyl coenzyme A or malonyl coenzyme A derived (polyketides, PK). NRP and PK represent about 50% of all current antibiotics (Table 1). The third are hybrids between NRP and PK and the fourth are composed of several carbohydrates units substituted with amine groups (aminoglycosides). And finally, the last group is composed of various molecules, such as terpenoids, fusidic acid or alkaloids such as metronidazole. In addition to these molecules used as antibiotics, thousands of antimicrobial peptides are known from insects, mammals, plants or amphibians [47]. These peptides are usually classified as "ribosomally synthesized and post-translationally modified peptides" (RiPPs), a subgroup of natural products [48].

Antibiotics

The NRP and PK are synthetized by multi-enzymatic complexes (non-ribosomal peptides synthetase, NRPS and polyketides synthetase, PKS) encoded by biosynthetic gene clusters [49]. These complexes are organized in modules including several domains. For example, the erythromycin synthase complex consists of three proteins and seven modules each containing three to six domains. [49]. The NRPS use amino acids as substrate elongated by peptidic connection, whereas PKS use acyl-coenzyme A as substrate elongated by Claisen condensation reaction [49]. This complex organization allows the production of a great number of different products, and therefore a great diversity. For example, ciclosporin belongs to the NRP category [50]. Hybrid assembly line that uses both amino acids and acetyl coenzyme A, or fatty acid synthetases (FAS), are also described [51]. NRP antibiotics comprise molecules such as β-lactams, daptomycin, lincomycin, polymyxins, and vancomycin while macrolides, mupirocin and tetracyclines belong to polyketides antibiotics.

Rifampicin belongs to hybrid NRP/PK (Table 1).

Antimicrobial peptides

Antimicrobial peptides are broad spectrum antibacterial molecules that have been discovered in blood cells in 1957 by Robert Skarnes [52]. They belong to natural products that are small peptides (i.e. less than 100 amino acids) ribosomally synthesized with posttranslational modifications (RiPPs). Natural peptides have a multifunctional activity that participates in innate immunity in eukaryotic and prokaryotic cells. [47]. Antimicrobial peptides are evolutionary well-conserved amphipathic molecules with hydrophobic and cationic amino-acids [53]. They can be categorized according to their secondary conformation: group I (alpha helical), group II (beta sheet), group III (mixed) and IV (extended) [54]. They have been isolated from almost all living organisms from prokaryotes to vertebrates. Indeed, thousands of antimicrobial peptides are known and come from insects, plants, or amphibians [45,47]. The main known mechanisms of action are related to their cationic charge and amphipathic structure, responsible for the membrane disruption of the negatively charged bacterial cell. Antimicrobial peptides can also interact with membraneassociated protein targets, as well as intracellular targets after penetration into the bacterial cytoplasm [54]. Finally, antimicrobial peptides can also have immunomodulatory effects on the innate immune system of the host [55].

Bacteriocins are antimicrobial peptides that were first discovered in bacterial species.

They are used in the agro-alimentary industry as food preservatives and in veterinary medicine [56]. Bacteriocins are separated into four groups: class I are small heat-stable posttranslationally modified peptides (<5kDa) which use the amino acid lanthionine, there are therefore called lantibiotics; class II are not modified heat-stable small peptides (<10kDa) which do not use lanthionine; class III are large heat-labile peptides (>30kDa) and class IV are complex or cyclic peptides containing lipids or carbohydrates [56]. Bacteriocins inhibited closely related species [57]. For example, lacticin 3147 and nisin are lantibiotics that exhibited an antibiotic activity against Gram-positive bacteria, notably Meticillin-resistant

Staphylococcus aureus (MRSA) or Vancomycin-resistant Enterococcus [58]. Nisin is the most famous lantibiotic, largely used as food preservative because of its activity against Listeria monocytogenes, MRSA and Streptococcus pneumoniae [59]. Nisin is also used in veterinary medicine under the name Wipe Out ® for the prevention of dairy mastitis [57]. The synergistic effects of lantibiotics with antibiotics have also been demonstrated in vitro [60].

According to the Antimicrobial Peptide database, 2,478 antibacterial peptides are already known [61]. All medical fields combined, 60 peptides have obtained the FDA approval and 140 are in clinical trials, mainly for oncological and metabolic diseases [62].

Yet, when focusing on infectious diseases, only 12 naturally occurring antimicrobial peptides have reached the stage of human clinical trial. (Table 2). Among them, only three (LYX-109, LL-37 and nisin) demonstrated a better efficacy than placebo, but none obtained the FDA approval for human application. Only gramicidin has received FDA approval for topical application in association with polymyxin and neomycin for ophthalmic use. Teixobactin is a new promising depsipeptide that provides an inhibition of S. aureus and M. tuberculosis [63].

This molecule uses notably the rare amino acid L-allo-enduracididine, which is challenging to synthesize and therefore limits its use despite efforts made to develop analogues [64]. Despite their narrow or broad spectrum of activity against human pathogens and easier bioengineering compared to NRPS or PKS, bacteriocins are not used in humans as antibiotics due to several limitations.

The main limitations in the use of antimicrobial peptides as antibiotics in clinical practice are their instability (proteolytic digestion, oxidation), their high cost and low yield of production, their short half-life, and their quick elimination [60]. Notably, their low bioavailability after oral ingestion related to proteolytic degradation is a great bottleneck. To solve these problems, production of analogues using rational drug design or nano-engineering is used to improve the pharmacokinetic properties. For instance, nano-engineering has increased the nisin spectrum to Gram-negative bacterial species [65] or allowed HPA3P HIS to be highly effective against Vibrio vulnificus in a mouse model [66]. The use of nanoparticles also prolonged the stay in the stomach of pexiganan after oral administration, which reduces the concentration of pexiganan required in a mouse model for Helicobacter pylori eradication [67]. Another approach is the combination of bacteriocins with other antimicrobials in order to reduce the resistance risk and to increase the antimicrobial potency [60]. Another matter of concern with AMP is the risk of development of resistance against our own immunity peptides. For instance, pexiganan have been previously found to induce cross-resistance to human-neutrophil-defensine 1 [68].

Methods for the discovery of antibiotics

Culture-based approaches

In the 1940s, Selman Waksman systematically screened the soil bacteria for antagonisms. Its culture-based approach is still in use today [69]. All the methods are based on the same principle: showing an inhibition of a tested strain over an indicator strain closely cultivated. The tested strain is the strain suspected to produce antimicrobials targeting the strain used as indicator. Several techniques exist to detect antimicrobial activity, either in solid or in liquid culture. There are three main methods regarding solid culture approaches:

the cross-streak method, the spot-on-the-lawn and the well diffusion method (Figure 2).

The cross streak is the inoculation of the bacterial strain tested vertically on the agar plate. The incubation time of the plate depends on the life cycle of the bacterial strain required to reach the exponential phase, which is the moment where secondary metabolites are excreted. Then, the indicator strain is inoculated into horizontal streaks and the plate is incubated (Figure 2) [70]. This technique is easy and powerful for screening but requires that both bacterial strains have the same culture conditions (e.g., atmosphere, temperature and growth duration).

The second and the third methods are respectively called "spot-on-the-lawn" and "well diffusion method". The "spot-on-the-lawn" method consists in depositing a drop of the tested strain on a lawn of the indicator strain [71]. After incubation, an inhibition zone is searched around the sediment. The "well diffusion method" is based on the diffusion of antimicrobials through agar which inhibits sensitive species. An agar plate is pooled with the indicator strain or inoculated with a lawn of the indicator and agar holes are punched out aseptically. Then, two main variants exist. The first is the Agar Plug Diffusion method which consists in removing a cylinder of agar from a plate previously inoculated with the tested strain. This cylinder of agar is then placed into the hole of the indicator plate [72]. The second variant method consists in placing a liquid broth of the tested strain or a growth supernatant in the hole [73]. After an optional rest time at +4°C, the agar plate is incubated and inhibition growth zones are measured (Figure 2). Several variants were developed, like using stress conditions or iron chelator [74,75]. The main limitation of solid culture tests concerns bacterial species that have different growth conditions or fastidious species.

Liquid culture-based approaches can solve this problem. Liquid broth co-culture has been used since the existence of the Waksman platform [69]. This is the simultaneous culture of the tested species and the indicator strain separated by a filter allowing the diffusion of nutrients but not the diffusion of cells. Following incubation, the bacterial growth of the indicator strain is determined by numeration, coloration or optical density [69]. Another method is to add the growth supernatant of the test species previously filtered and concentrated to a liquid culture of the indicator strain [76]. The latter method allows the bacteria tested to be grown under conditions different from those of the indicator strain (Figure 3).

Discovering antimicrobial effects from already known compounds

Some antibiotics were discovered years before they were used (fidaxomycine, daptomycin, or linezolid). Several million of chemical compounds are known in chemical databases and could provide a potential source of antibiotics [32]. Moy et al. have tested the activity against E. faecalis of more than 6,000 chemical compounds and 1,136 natural products in the Caenorhabditis elegans animal model, discovering 16 molecules increasing the survival of animals [77]. The bottleneck remains the selection and the high throughput testing of these molecules.

Synthesis of new molecules and improvement of already known compounds

The « Rational Drug Design » consists in the empirical synthesis of new molecules that are designed according to several rules to be well-absorbed, non-toxic, and active against a specific target [32]. The most famous rules used by the industry are Lipinsks's rules.

Despite more than 10 million of new molecules synthesized, only a few active molecules have reached the market, notably antituberculous drugs [32,37] (Table 1). This can be explained by the fact that antibiotics have generally poor economics [78].

The improvement of already known molecules is another strategy that can yield benefits. The modification of cephalosporin lead to the development of cefiderocol, that demonstrated safety and tolerability in healthy subjects, and clinical trials for the treatment of urinary tract infections are ongoing [79]. Another example is the modification of the aminoglycoside sisomicin that leads to the development of plazomicin [80]. This antibiotic was recently approved by the FDA and a small phase 2 clinical trial found it had an efficacy comparable to that of levofloxacin in the treatment of urinary tract infections and acute pyelonephritis [81]. If the potential use of these antibiotics remains to determine, their mechanism of action is not novel, and the apparition of resistance is expected in the same way as for their related antibiotic parent.

4.4.Genome mining

Secondary metabolites are encoded by Biosynthetic Gene Cluster (BGCs). Thousands of prokaryotic genomes are available in sequence databases. These data have generated thousands of BGCs that potentially encode unknown molecules [82,83]. Despite the fact that many of them do not have any antimicrobial activity, little is known about them. Walsh et al. Bacillus licheniformis that was discovered using the mode-of-action genome mining approach. The authors screened the databases for LanM genes, which are involved in the biosynthesis of lantibiotics [86]. The identification of putative bacteriocins encoded by BGC from the genome sequence is possible using bioinformatic algorithms [87]. Bacteriocins are easily found using bioinformatic tools compared to NRPS or PKS. Tools such as BAGEL, antiSMASH or PRISM are widely used for this purpose. These tools exploit two main approaches [83]. The first consists in finding new congeners of already known scaffolds. This approach is based on the homology comparison by the research of conserved domains (anchors), as for the thiotemplate domain of NRPS and PKS [88]. Small structural changes of the new homologue may result in a significant change in the activity of the product. The second approach is more difficult and consists in finding new scaffolds. Predicting the chemical structure and biological activity of a BGC informatic sequence is a real challenge [83]. The main problem that remains is proving the functional activity of BGC [89]. Both approaches often require the engineering expression of BGC from the native host or from a heterologous host, which represents the main bottleneck of genome mining for the discovery of new antibiotics.

Recently, Hover et al. have screened more than 2,000 soil samples from various areas of the US, searching for BGCs encoding calcium-binding motif Asp-X-Asp-Gly [90]. This motif is related to calcium-dependant antibiotics such as lipopeptides, for which the mechanism of action is not fully understood [91]. They found several clades of uncharacterized BGC, of which the most abundant was present in 19% of all samples. This clade was named malacidins, the molecules were then synthesised, and their antibiotic activity was characterized in vitro. The malacidin A exhibited a broadly antibiotic activity against Gram-positive bacteria, notably MRSA, which was successfully confirmed in a skin-wound infection rat model. In conclusion, genome mining is a promising approach for new antibiotic discovery, despite the fact that the method is fastidious and time-consuming.

4.5.CRISPR Cas9

Bacteria and fungi have an immune system that protects them from foreign genetic material that could be inserted by phages. This immune system consists of restriction enzymes, toxin-antitoxin and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) Cas system [92]. The utilization of CRISPR Cas9 to design new antimicrobials with a predetermined activity spectrum has been already performed with promising results.

Citorik et al. have developed RNA-guided nucleases that target the resistance gene bla SHV-18

and bla NDM-1 . After transformation by plasmids and transduction by bacteriophages, the authors observed a significant reduction in the number of E. coli containing the targeted resistance gene, either chromosomal or plasmid [93]. The same approach has been successfully tested using phagemid targeting the S. aureus methicillin resistance gene [94].

The same authors tested the use of bacteriophages in a mouse model of S. aureus skin infection with an efficacy comparable to that of mupirocin [94]. Other authors used genome editing technology to re-sensitize MDR cells. As an example, Kim et al. used CRISPR Cas9 to target a conserved sequence of Extended-Spectrum β-Lactamases, thus restoring the susceptibility of E.coli in their in vitro model [95].

Conclusion and perspective

More than three quarters of all antibiotics currently used in human health are natural products or derived from them. The discovery of antibiotics declined after the 1970s due to the difficulty of cultivating bacterial species from soil under laboratory conditions. New innovative culture approaches were then created thanks to the bloom of new molecular methods. In this way, genome mining searching for new BGCs as well as CRISPR Cas9

technology are promising new approaches. Recently, the ability to rapidly identify bacterial strains using Matrix Assisted Laser Desorption Ionisation Time of Flight (MALDI Tof) has permitted the rebirth of culture. Therefore, new culture approaches trying to mimic the natural environment were invented in order to grow fastidious species. This led to the discovery of new bacterial species. For instance, Ling et al. discovered the new antibiotic teixobactin from the new species Eleftheria terrae isolated in the soil using a diffusion chamber [63].

The same approach is now possible for the human-associated microbiota. The nose is an example of ecological niche poor in nutrients in which the microbiota is probably in strong competition [75]. Using a home-made nasal synthetic medium under iron-limited condition, Krismer B et al. discovered lugdunin, a new antibiotic inhibiting S. aureus growth [74]. The gut microbiota is another microbiota of interest for antibiotic research. Indeed, the human gut has an average load concentration ranging from 10 4 to 10 12 CFU/mL from the duodenum to the colon. These species live in extreme competition, as they did before human colonization where bacteria lived in a competitive world that led them to naturally develop many antimicrobial products. Metagenomic analysis from the human gut microbiota found many BGCs. In 2014, Donia et al. found 3,118 BGCs including NRPS, RiPPs and PKs in the human microbiome. They also found 599 BGCs in the gut. Taken together with the oral cavity, it is one of the richest sites in BGCs of the human microbiota. They also found and purified lactocillin, a new thiopeptide antibiotic, isolated from the vaginal microbiota [96].

The study of the gut microbiota using culture methods was recently improved by culturomics, a novel approach that consists in the multiplication of growth conditions [97].

This has led to the discovery of previously uncultivated species. With this approach, Lagier et al. significantly increased in a couple of years the gut repertoire from 690 to 1,525 species, of which 247 were totally new [98]. Indeed, the new species described from the gut represent an opportunity for the research for novel antibiotics. The search for new antibiotics naturally synthesized by organisms living in complex ecosystems like the gut microbiota, using the culture approach, seems the modern continuity of what has already worked in the past. Thus, if the study of antagonisms between environmental bacteria has led to the discovery of a substantial proportion of antibiotic classes, such studies were rarely performed from humanderived microbiota.

In conclusion, the research for new antibiotic molecules is a key point among the strategies for the fight against antibiotic resistance. The recent advances from both culturedependant and culture-independent methods of exploration of complex ecosystems such as soil or human-associated microbiota open a new era in antimicrobial research.

  1889, Jean Paul Vuillemin defined the word "antibiosis" as any biological relationship in which "one living organism kills another to ensure its own existence". Several antagonisms between microorganisms, notably moulds, were published in the thesis works of Ernest Duchesne in 1897. He discovered the inhibition of Escherichia coli by Penicillium glaucum thirty years before Fleming. Despite several observations of antagonisms between microorganisms, no antimicrobial molecule was purified. The first antimicrobial molecules discovered were chemical compounds. In 1909, Paul Ehrlich discovered the arsphenamine, an arsenic derivative active against Treponema pallidum, the agent of syphilis. This antibiotic was commercialized in 1911 under the name Salvarsan ® then Mapharsen ® . In 1930, Gerhard Domagk discovered the antibiotic effects of sulphanilamide, a molecule synthetized 22 years before by Paul Gelmo. This antibiotic was marketed under the name Protonsil ® in 1935 and was used by soldiers during World War II [32].

  found 74 putative BGC from 59 genomes from the Human Microbiome Project[84]. These BGC belonged mainly to Firmicutes, Proteobacteria and Bacteroidetes and the most commonly putative bacteriocins encoded belonged to classes III and IV. Several approaches of genome mining are possible. The most used are sequence-based approach, ecology-based genome mining, mode-of-action-based genome mining, or functionbased genome mining

Figure legend Figure 1 .

 legend1 Figure legend

Figure 2 .

 2 Figure 2. Solid culture approaches highlight inhibition between two bacterial species.

Figure 3 .

 3 Figure 3. Liquid culture approaches highlight inhibition between two bacterial species.

  1889, Jean Paul Vuillemin defined the word "antibiosis" as any biological relationship in which "one living organism kills another to ensure its own existence". Several antagonisms between microorganisms, notably moulds, were published in the thesis works of Ernest Duchesne in 1897. He discovered the inhibition of Escherichia coli by Penicillium glaucum thirty years before Fleming. Despite several observations of antagonisms between microorganisms, no antimicrobial molecule was purified. The first antimicrobial molecules discovered were chemical compounds. In 1909, Paul Ehrlich discovered the arsphenamine, an arsenic derivative active against Treponema pallidum, the agent of syphilis. This antibiotic was commercialized in 1911 under the name Salvarsan ® then Mapharsen ® . In 1930, Gerhard Domagk discovered the antibiotic effects of sulphanilamide, a molecule synthetized 22 years before by Paul Gelmo. This antibiotic was marketed under the name Protonsil ® in 1935 and was used by soldiers during World War II [32]. In 1928, Alexander Fleming accidentally discovered in his forgotten colonies of Staphylococcus aureus that a fungus was inhibiting the growth of Staphylococcus. The Penicillium notatum molecule has been purified and called penicillin. But the industrial production of this antibiotic was performed only in 1940 by Howard Florey et Ernst Chain,

  industry turned to the in vitro synthetization of new molecules, based on knowledge of the known mechanism of action of antibiotics. Unfortunately, few new classes of antibiotics have been discovered, the nitrofuran in 1953, the quinolone in 1960, the sulphonamide in 1961 and oxazolidinones in 1987. The modification and improvement of already known molecules has also been carried out. This is reflected by the commercialization of linezolid in 2003 and daptomycin in 2001, although these molecules had been known since 1955 and 1986,

  found 74 putative BGC from 59 genomes from the Human Microbiome Project[84]. These BGC belonged mainly to Firmicutes, Proteobacteria and Bacteroidetes and the most commonly putative bacteriocins encoded belonged to classes III and IV.Several approaches of genome mining are possible. The most used are sequence-based approach, ecology-based genome mining, mode-of-action-based genome mining, or functionbased genome mining[83,85]. For instance, lichenicidin is a bacteriocin synthesized by

Figure legend Figure 1 .

 legend1 Figure legend

Figure 2 .

 2 Figure 2. Solid culture approaches highlight inhibition between two bacterial species.

Figure 3 .

 3 Figure 3. Liquid culture approaches highlight inhibition between two bacterial species.

Table legend Table 1 .

 legend1 Discovery date, origin of the organism and synthesis pathway of antibiotics.

Table 2 .

 2 Clinical trials involving antimicrobial peptides.

  years old permafrost samples[22]. Kashuba et al. have found several resistance genes in the genome of a Staphylococcus hominis isolated from permafrost[23]. Of the 93 strains cultured by Bhullar et al. from the 4 million-year-old Lechuguilla cave (New Mexico), 65%

'Costa et al.

have found resistance genes to β-lactam, tetracyclines and glycopeptides from 30,000

Table legend Table 1 .

 legend1 Discovery date, origin of the organism and synthesis pathway of antibiotics.

Table 2 .

 2 Clinical trials involving antimicrobial peptides.

Acknowledgements

The authors thank Magdalen Lardière for reviewing the English language of the manuscript.

Declarations

Funding: This work was supported by the French Government under the « Investissements d'avenir » (Investments for the Future) a program managed by the Agence Nationale de la Recherche (ANR, fr: National Agency for Research), (reference: Méditerranée Infection 10-IAHU-03).

Acknowledgements

The authors thank Magdalen Lardière for reviewing the English language of the manuscript.


Thibaud Mathis

Laurence Rosier

Fatima Meniai

Stéphanie Baillif

Celia Maschi

Joël Herault

Jean-Pierre Caujolle

Laurent Kodjikian

Julia Salleron

Professor Juliette Thariat
email: jthariat@gmail.com

The Lens Opacities Classification System III Grading in Irradiated Uveal Melanomas to Characterize Proton Therapy-Induced Cataracts

Keywords: cataract, LOCS III, Lens Opacities Classification System III, grading, radiation therapy, proton therapy

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Management of uveal melanomas is increasingly conservative, and proton beam therapy (PBT) and brachytherapy are the most frequently used techniques 1,2 . However, radiationinduced toxicities, such as optic neuropathy, retinopathy/maculopathy, dry eye syndrome, and cataracts can compromise vision 3-5 . As the lens is one of the most radiosensitive tissues among the ocular structures, cataracts are a frequent complication after ocular radiation therapy. Their incidence varies from 45% to 100% after ocular radiation therapy 1,6, [START_REF] Seibel | Cataract development in patients treated with proton beam therapy for uveal melanoma[END_REF] . Radiation cataracts typically include posterior subcapsular lens clouding caused by damage to the subcapsular epithelium. However, there is neither absolute phenotypic conformity for the subtype of cataracts nor pathognomonic signs of radiation-induced cataracts. Senile, traumatic, or iatrogenic cataracts may also occur after radiation therapy. Full analysis of how exposure to therapeutic ionizing irradiation correlates and colocalizes with subsequent lens opacification is warranted to better establish causality. Such colocalization between radiation beam and opacities is only possible with specific forms of radiation modalities, in particular particle therapy that yields sharp dose distributions. Another important gap in current knowledge is that radiation cataracts are not graded like non-oncological cataracts [START_REF] Seibel | Cataract development in patients treated with proton beam therapy for uveal melanoma[END_REF] . The international Common Toxicity Criteria (CTC) classification does provide grades of severity in terms of visual acuity and cataracts but is not appropriate for uveal melanomas as it does not distinguish between vision loss due to maculopathy or cataracts, and does not describe lens opacities accurately. Depending on their location in the lens, opalescence, color and proportion of lens involved, lens opacifications can variably affect the vision. The international Lens Opacity Classification System (LOCS) defines a score based on the anatomic location and extent of cataracts on slit-lamp examination. The third version of the LOCS (LOCS III) is a robust and accurate means to classify cataracts as nuclear color, nuclear opalescence, cortical and posterior subcapsular cataracts, and grade them in terms of extent into the lens based on an atlas of standardized slit-lamp retroillumination images [START_REF] Chylack | The Lens Opacities Classification System III. The Longitudinal Study of Cataract Study Group[END_REF] . Assessing LOCS III in radiation-induced cataract could provide a better way to describe the effect of the proton beam on lens opacities. This study was designed to evaluate the feasibility of using the LOCS III for radiationinduced cataracts and to examine correlations between the proton beam impact onto the lens and anatomical subtypes and extent of cataracts according to the LOCS III after PBT for uveal melanomas.

MATERIALS & METHODS Patient selection and cataract grading

This interventional case series included consecutive patients with cataract from one hospital (Bordeaux, France) who underwent PBT for eye tumor between 2007 and 2016. Patients who already had cataracts or were pseudophakic prior to PBT, and patients who had intravitreal, subtenon or subconjunctival corticosteroid use were excluded from the study. All included patients provided fully-informed consent before participation and an international review board approved the study (Ethics Committee of the French Society of Ophthalmology, IRB 00008855 Société Française d'Ophtalmologie IRB#1).

Patients were evaluated for cataract development at a single ophthalmology hospital, expert in LOCS III grading (LR), after pupil dilation with 0.5% tropicamide and 10% phenylephrine hydrochloride 30 minutes before examination. A pupil diameter of more than 8 mm was considered as appropriately dilated for cataract evaluation. LOCS III grading scales include lens opacities defined as nuclear opalescence (NO), nuclear color (NC), cortical (C) and posterior subcapsular cataracts (P) with six degrees of extent, i.e. severity. The LOCS III uses a set of six slit-lamp images of nuclear cataracts and five retro-illumination images of cortical or posterior subcapsular cataracts. Patient characteristics, tumor and cataract grading were prospectively recorded in a case report form (CRF), which was filled-out immediately after the medical appointment. Collected data included age, gender, initial and final visual acuity, and tumor characteristics (diagnosis, TNM staging, ultrasound thickness and diameter, volume, topography, and ciliary involvement).

Treatment

Irradiation was conducted with a 65 MeV dedicated hospital-based cyclotron at the Cancer Center in Nice, France. Four tantalum fiducial markers were positioned under anesthesia onto the sclera using transillumination to define tumor borders. After surgery, topical corticosteroids were administered for two weeks. Tumor characteristics and associated signs were reported on ophthalmology reports based on transillumination, fundus (or retinography/angiography), ultrasound, and/or optical coherence tomography depending on tumor position relative to the equator of the eye. PBT was performed two to four weeks after fiducial placement. The Eyeplan treatment planning system software v1-3 was used. Ocular CT-scan with clips was performed for the delineation of normal structures and treatment plan optimization. The tumor was delineated and 2.5mm lateral safety margins were added around the tumor. Beam modifiers were designed depending on the target range and lateral conformation was performed using a brass collimator adjusted to the tumor contours. The papilla, optic nerve, and macula were preserved whenever possible without compromising tumor control. In case of equatorial and pre-equatorial tumors, optimization using CT-scan modelling was performed on the anterior chamber with the lens as a surrogate. The lens was preserved whenever possible using adapted gaze, but not at the cost of tumor under coverage or sacrifice of optic nerve or macula. The patient's gaze was focused using a light-emitting diode located in a plane perpendicular to the beam. Proper projection of the beam using light field projection was systematically verified. Patient and tumor setup were controlled using online orthogonal X-ray images. Eye position was monitored using video camera surveillance during the 10-second treatment, eye movements triggering immediate beam interruption. The gaze direction was chosen to minimize the dose to the optic nerve and macula, and when possible the dose to the lens and retina. Each tumor was irradiated by four fractions of 13 Gy physical dose; the corresponding radiobiologically equivalent dose was 15 GyRBE that corresponds to the dose that would be given with conventional photon-based irradiation.

Patients had antibiotic and corticosteroid eye drops for a period of one month after the end of treatment. All data concerning irradiation planning were collected in patient medical charts.

Dose-volume analysis

Lens periphery and lens core volumes were generated from the outer contours of the lens, which were delineated with a similar method throughout the study. Given the craniocaudal length of the lens and the CT-scan slice thickness, five slices were sufficient in all cases to delineate the lens on all slices where it was visible. The same two investigators (dosimetrists experts in the field) delineated patient lenses throughout the study. The treatment planning system for ocular PBT was able to reconstruct the lens volume, shape, and position to produce dose volume histograms, i.e. relationships between doses and volumes of the lens to be correlated with clinical outcomes such as cataracts. Computer-generated dose-volume histograms of the tumor and other structures (eyeball, ciliary body, etc.) were also extracted using the Eyeplan software. Graphic displays of treatment plans were analyzed for collimator aperture and isodose projections onto the eye. The volume of the eye lens and periphery lens that received at least 20%, 50%, and 90% of the maximum prescription dose (52 Gy) defined as V10 Gy, V26 Gy, and V47 Gy, were calculated from full dose-volume histograms. Additionally, the volume of the ciliary body V10 Gy, V26 Gy, and V47 Gy was reported.

Analysis of cataract subtypes according to the LOCS III

All cataracts were graded by a single trained ophthalmologist (LR). Description of cataracts with slit-lamp examination was performed by an ophthalmologist blinded to lens irradiation avoidance on the proton therapy plan. We examined whether the proton beam anterior projection included the lens on graphic displays, and if so what proportion of lens was irradiated. We correlated the beam projection with grade of severity defined by the extent of the lens opacities after PBT. We then established whether the LOCS III location of cataracts were consistent with radiation damage, i.e. whether the classical anatomical subtype of cataracts, such as the posterior subcapsular subtype, was located within the beam projection. Similarly, we examined whether cataract subtypes atypical with respect to radiation-induced damage (nuclear for example) could be attributed to the proton beam in the terms of beam projection and location of opacities. Finally, we analyzed the extent of cataracts and correlated them with dose-volume histograms of the lens periphery or core volume.

Statistical analysis

The patient sample size was determined to evaluate the feasibility of integrating the LOCS III in patients with cataracts in a routine onco-ophthalmology practice with sufficient sampling of the various cataract subtypes. Visual acuity was converted to logMAR units for statistical investigations. Quantitative parameters were described by median and interquartile range (IQR) according to the normality of distributions assessed by the Shapiro-Wilk test. Qualitative parameters were described by frequency and percentage. For each of the four features of the lens (the extent of nuclear opalescence (NO), nuclear color (NC), cortical (C) and posterior subcapsular (P) cataracts), the relationship between extent and patient characteristics was investigated using bivariate analyses. For binary parameters, the Wilcoxon test was used, and for qualitative with more than 3 levels the Kruskal-Wallis test was used. To test the relationship between the extent and quantitative parameters, the Spearman correlation coefficient was computed. When several patients or dose-volume characteristics were predictive of the extent with a significant level less than 0.1, they were included in a multivariate linear model. The multicollinearity was assessed with the variance inflation factor (VIF) and parameters with a VIF ≥3 were excluded. The stability of the final model was investigated with the bootstrap resampling method. The validity of the final model was checked by the Studentized residuals and Cook's distance. All analyses were performed using SAS 9.4 software (SAS Institute Inc., Cary, NC, USA).

6

RESULTS

Population

Fifty-two patients were included. Patient characteristics are reported in Table 1. Melanoma types were choroidal (75%), choroido-ciliary (10%), ciliary (8%), irido-ciliary (5%), and iris (2%). For choroidal melanomas, the anterior edge of tumor was posterior to the equator in 29 patients (56%) and on the equator for six patients (11%). None of the tumors were in contact with the lens at diagnosis and at the time of cataract grading. All patients were treated by PBT after tantalum fiducial placement and none of them had any complications related to this surgery.

Cataract analyses according to the LOCS III

The median time to diagnosis of cataracts after PBT was 36 months (22;83). Different subtypes of cataracts were graded accorded to the LOCS III at the slit lamp examination (Figure 1) and are reported in Figure 2. The crystalline lenses were outside or within the anterior projection of the proton beam in 10 patients (19%) and 81 patients (81%) of the patients, respectively. The proportion of lens in the proton beam projection was variable depending on tumor volume and location. This proportion exceeded 50% in 8 patients (15%), was between 25% and 50% in 22 (42%) patients and was less than 25% in 22 patients (42%). The proportion of lens within the proton beam projection was significantly correlated with the extent of posterior subcapsular cataracts (P) according to the LOCS III (p=0.01; Table 2)

Cataracts according to the LOCS III and to clinical parameters

No relationship was found between time to diagnosis and cataract subtype according to LOCS III grading. In bivariate analysis, a significant correlation was observed between tumor volume, maximum tumor diameter and the occurrence of posterior subcapsular cataracts (P). The initial thickness of lens was not significantly associated with post-proton cataracts. Tumor stage was a significant predictive factor for the extent of subcapsular cataracts (P) according to the LOCS III; T3 stage was significantly associated with the extent of posterior subcapsular cataracts (P) (p<0.01). There was no significant correlation between tumor type (iris, ciliary body or choroidal melanoma) and cataract subtype. However, for choroidal melanomas, an equatorial tumor correlated with the extent (grade of LOCS III severity) of posterior subcapsular cataracts (P) (p<0.01) (Table 3). After a multivariate analysis, tumor volume (p<0.01) and an equatorial tumor location (p=0.01) were found to be independently associated with the occurrence of posterior subcapsular cataracts (P).

Cataracts according to the LOCS III and dose-volume parameters in patients with an irradiated lens

Focusing on the 42 patients whose crystalline lens was at least partially in the proton field, dose-volume characteristics are described in Table 4. The extent/severity of posterior subcapsular (P) and nuclear color cataracts (NC) were significantly correlated with the volume of ciliary body receiving 10 Gy and 26 Gy, which corresponded to 20%, 50% of the maximum prescribed dose. Thus, the higher the dose to the ciliary body, the more severe the subcapsular (P) and nuclear color (NC) cataracts. Dose to the ciliary body was not significantly correlated with other subtypes of cataracts (NO and C) (p>0.05). In addition, it was observed that the extent of posterior subcapsular cataracts (P) was significantly correlated with the proportion of lens periphery receiving at least 10 Gy, 26 Gy, and 47 Gy. The larger the volume of lens irradiated the more severe the posterior subcapsular cataracts. After adjusting the results of dose-volume parameters on tumor volume and a posterior tumor location, the volume of lens receiving 10 Gy and 26 Gy remained significantly associated with the extent/severity of posterior subcapsular (respectively, p=0.04 and p=0.03). The other parameters were no longer significantly associated after adjustment: volume of ciliary body receiving 10 Gy (p=0.09), that receiving 26 Gy (p=0.06), the volume of lens periphery receiving 10 Gy (p=0.07), that receiving 26 Gy (p=0.053), and the volume of lens receiving 47 Gy (p=0.13). No stable multivariate model was found for the extent/severity of nuclear color (NC) cataracts due to strong collinearity.

DISCUSSION

Ocular proton therapy using a dedicated ocular cyclotron has physical properties that allow a lens-sparing approach owing to more accurate dose distribution, and which are not found in other photon-based modalities. This is due to a small lateral penumbra to the order of one millimeter or less at the radiation field edges. Radiation-induced cataracts were first described in 1952 [START_REF] Cogan | Clinical and pathological characteristics of radiation cataract[END_REF] . Until very recently, the threshold for detectable lens opacities was assumed to be to the order of 2 Gy (with conventional X-ray photon irradiation) for acute exposure to ionizing radiation and 5 Gy for highly fractionated or protracted, chronic, exposure [START_REF] Merriam | A clinical and experimental study of the effect of single and divided doses of radiation on cataract production[END_REF] ; for visionimpairing cataracts, these thresholds were to the order of 5 Gy 10 . More recent epidemiological studies have demonstrated that doses of conventional radiation therapy to the order of 1 Gy can lead to detectable lens opacities [START_REF] Ainsbury | Ionizing radiation induced cataracts: Recent biological and mechanistic developments and perspectives for future research[END_REF][START_REF] Bouffler | Radiation-induced cataracts: the Health Protection Agency's response to the ICRP statement on tissue reactions and recommendation on the dose limit for the eye lens[END_REF] . Several other radiation-related factors have been involved in the occurrence of radiation cataracts, such as the type of irradiation, total dose, dose per fraction, and time since exposure. Although, with PBT, lens irradiation was completely avoided in about a fifth of the 52 consecutive patients included in the present study, all patients had cataracts per study selection criteria. Despite the possibility to avoid lens irradiation with PBT for uveal melanomas, radiation-induced cataracts are, however, frequent as there are numerous situations where the lens is next to the tumor or within the anterior projection of the proton beam. Similar results have also been reported in other series of uveal melanoma patients after PBT [START_REF] Seibel | Cataract development in patients treated with proton beam therapy for uveal melanoma[END_REF][START_REF] Conway | Estimates of ocular and visual retention following treatment of extra-large uveal melanomas by proton beam radiotherapy[END_REF][START_REF] Riechardt | Proton beam therapy of parapapillary choroidal melanoma[END_REF] . In this cohort, all patients were treated uniformly with a similar method, total prescription dose, and lens-sparing approach.

The LOCS III has been validated in both clinical and epidemiological studies of cataracts of various origins [START_REF] Chylack | The Lens Opacities Classification System III. The Longitudinal Study of Cataract Study Group[END_REF][START_REF] Tang | Prevalence of Age-Related Cataract and Cataract Surgery in a Chinese Adult Population: The Taizhou Eye Study[END_REF][START_REF] Gali | Cataract grading systems: a review of past and present[END_REF] but is not commonly used in ocular oncology. We showed herein the feasibility of using the LOCS III to evaluate cataracts after PBT for uveal melanomas. In particular, we found correlations between the proton beam projection and the anatomical location of the lens opacities, i.e. LOCS III subtypes NC, NO, C, and P. We also found relationships between the volume of lens included in the proton field and extent of lens opacities as defined by the LOCS III severity. It was beyond the scope of the current study to correlate cataract severity and the deterioration of the visual acuity after PBT owing to major confounding factors such as radiation maculopathy and optic neuropathy, which, contrary to cataracts, are often irreversible [START_REF] Gragoudas | Cataract extraction after proton beam irradiation for malignant melanoma of the eye[END_REF] . Additionally, the patient sample size was neither designed to assess the influence of ocular radiation side effects nor to show the importance of wellknown confounding factors (age, diabetes, etc…) on visual acuity. However, to the best of our knowledge, this is the only study that assessed correlations between accurate characteristics of cataracts using the LOCS III and the ballistics of the proton beam taking advantage of its excellent lateral dose distribution. We showed that cataracts were diagnosed at a median 36 months post treatment, which is earlier than with more fractionated dose regimens [START_REF] Carnicer | Study of the secondary neutral radiation in proton therapy: toward an indirect in vivo dosimetry[END_REF] but consistent with other hypofractionated high-dose proton therapy series [START_REF] Carnicer | An indirect in vivo dosimetry system for ocular proton therapy[END_REF] .

Radiation-induced cataracts are typically reported to be of subcapsular type [START_REF] Hamada | Intercellular and intracellular signaling pathways mediating ionizing radiation-induced bystander effects[END_REF][START_REF] Gragoudas | Lens changes after proton beam irradiation for uveal melanoma[END_REF] . Pathogenesis suggests that radiation damages the DNA of proliferative cells that will migrate posteriorly leading to deformed lens fiber and debris accumulation in the subcapsular regions, especially posteriorly [START_REF] Merriam | Experimental radiation cataract--its clinical relevance[END_REF] . However, we did not exclusively observe posterior subcapsular cataract, which is consistent with a study investigating brachytherapy that found that among the 85% of anterior ocular tumor patients who had cataracts, only 52% were of subcapsular type but no detailed description of plaque placement and type/severity of cataracts was reported [START_REF] Finger | Palladium-103 for Choroidal Melanoma Study Group. Risk factors for cataract after palladium-103 ophthalmic plaque radiation therapy[END_REF] . This observation highlights the complexity of the mechanisms involved in post-radiation cataracts. Moreover, we cannot exclude that so-called radiation-induced cataracts may indeed be due to classical confounding factors but also other iatrogenic causes (traumatic cataracts by tumor compression or during clip placement, use of topical steroids, etc…). Furthermore, it is unlikely that the small dose received by secondary neutrons contributed to cataracts [START_REF] Carnicer | Study of the secondary neutral radiation in proton therapy: toward an indirect in vivo dosimetry[END_REF][START_REF] Carnicer | An indirect in vivo dosimetry system for ocular proton therapy[END_REF] but bystander effects on cells that are not directly irradiated but are at short distances from irradiated cells and communicate between each other by means of intercellular junctions or cytokines [START_REF] Hamada | Intercellular and intracellular signaling pathways mediating ionizing radiation-induced bystander effects[END_REF] is possible.

Among the 42 patients with an irradiated lens, the proportion of lens in the proton beam was significantly correlated with the occurrence of posterior subcapsular cataracts (P) according to the LOCS III. In addition, the extent of posterior subcapsular (P) and nuclear color (NC) cataracts was also significantly correlated with the dose to the ciliary body. Ciliary body involvement of the tumor or close proximity between the tumor and ciliary body can result in radiation damage to the ciliary body. Such damage may result in intra-ocular inflammation and secondary posterior subcapsular cataracts, as already reported [START_REF] Gragoudas | Lens changes after proton beam irradiation for uveal melanoma[END_REF] . Because ciliary body melanomas are anterior tumors in close proximity with the lens, gazing angle cannot be fully optimized to entirely avoid the lens and to exclude the lens nucleus from the proton beam projection. Moreover, ciliary body melanomas are peripheral tumors that are generally thicker than posterior or equatorial tumors as they are diagnosed later and thus require higher dose. For these reasons, lens exclusion from the proton beam projection can rarely be done in such localizations. We also observed that posterior tumor location was significantly correlated with the appearance of posterior subcapsular cataracts. This may be due to the fact that when tumors are very close to the posterior structures, treatment plan optimization is performed to spare the macula/optic disk rather than the lens.

While we did not find any correlation between uveal melanoma types treated (choroidal, iris, or ciliary body involvement) and LOCS III subtype, we observed a significant correlation between T3 stage and the occurrence of posterior subcapsular (P) cataracts. This finding may be a consequence of the volume of tumor and lens irradiated but also of inflammation associated with significant tumor necrosis as well as vessel damage in the treated eyes [START_REF] Saornil | Histopathology of proton beam-irradiated vs enucleated uveal melanomas[END_REF] . Kleineidam et al. also reported thickness and the anterior tumor location as prognostic factors of cataractogenesis after Cobalt 60 brachytherapy of 370 uveal melanomas [START_REF] Kleineidam | Cataractogenesis after Cobalt-60 eye plaque radiotherapy[END_REF] . However, use of corticosteroids to control intraocular inflammation was not reported [START_REF] Kleineidam | Cataractogenesis after Cobalt-60 eye plaque radiotherapy[END_REF] but prolonged use of these drugs is required to induce cataracts.

With respect to study limitations, the lack of controls was intrinsic to the study selection criteria as the aim of the current study was to correlate the subtype of cataracts according to LOCS III with the projection of the proton beam onto the crystalline lens and the proportion of lens within the proton field. The small number of cataract subtypes may be considered as a weakness; however, this longitudinal cohort was designed to assess the feasibility of using the LOCS III in oncology. The design of the study was not appropriate to eliminate confounding factors for cataract development [START_REF] Miglior | Risk factors for cortical, nuclear, posterior subcapsular and mixed cataract: a case-control study[END_REF] . For instance, examination of the healthy eye would have been useful in identifying cases of bilateral cataracts that are characteristic of senile or diabetic cataracts, but it is unlikely that these would have developed within 36 months, and this relatively rapid occurrence is more consistent with high-dose radiation-induced cataracts. [START_REF] Seibel | Cataract development in patients treated with proton beam therapy for uveal melanoma[END_REF][START_REF] Kleineidam | Cataractogenesis after Cobalt-60 eye plaque radiotherapy[END_REF][START_REF] Thariat | Cataract Avoidance With Proton Therapy in Ocular Melanomas[END_REF][START_REF] Thariat | Intensity-modulated radiotherapy of head and neck cancers: Dose effects on the ocular, orbital and eyelid structures[END_REF][START_REF] Thariat | Proton Beam Therapy for Iris Melanomas in 107 Patients[END_REF] In addition, the patients included herein are unlikely to have been affected by steroid-induced cataracts because of the relatively short prescription of corticosteroids after surgery for fiducial placement is not sufficient to induce cataracts [START_REF] Thariat | Cataract Avoidance With Proton Therapy in Ocular Melanomas[END_REF][START_REF] Urban | Corticosteroid-induced cataracts[END_REF] . Another potential limitation is that interobserver variability in the slit-lamp evaluation of cataracts may have led to interpretation bias, especially when evaluating the opalescence of the nucleus and severity score. However, the current study was designed to assess cataracts according to the LOCS III by a single ophthalmologist trained in the use of LOCS III for non-oncological cataracts.

Based on the present study, the LOCS III is of potential interest to better characterize and understand the mechanisms of radiation-induced cataracts. These initial findings need further validation in larger prospective cohort studies, and this could lead in the future to promote the use of lens-sparring techniques when possible [START_REF] Thariat | Cataract Avoidance With Proton Therapy in Ocular Melanomas[END_REF] . The radiation oncology community currently lacks recommendations for dose thresholds to be applied to the lens in therapeutic conditions using high total dose, high dose rate, and hypofractionation. Moreover, there is currently usually no distinction made between the different parts of the lens during PBT planning. Knowing correlations between visual impairment and location of opacifications might be used to optimize fixation angle and beam shaping when such change in planning is neither a risk for tumor coverage or macula and optic disc sparing. Using LOCS III may even be more relevant to new PBT modalities than passive delivery such as used in the current study and in most international reference centers. Active scanning is the method used in a few but expanding number of new PBT facilities, and it can achieve a slightly better dose sparing at beam entry and thus may allow more personalized lens-sparing based on LOCS III grading. Of note, however, such facilities still require adaptations (including energy optimization and lateral collimation) to achieve correct depth dose distribution (tumor and posterior structures). Confirmation of the correlation between visual impairment and the severity of cataracts assessed by the LOCS III [START_REF] Grewal | Correlation of nuclear cataract lens density using Scheimpflug images with Lens Opacities Classification System III and visual function[END_REF][START_REF] Pan | Correlation among lens opacities classification system III grading, visual function index-14, pentacam nucleus staging, and objective scatter index for cataract assessment[END_REF] in an oncology context could also be of great interest in eyes where other radiation complications may occur in view of a potential cataract surgery. More systematic use of the LOCS III in onco-ophthalmology should probably be encouraged.

CONCLUSION

We have shown herein the feasibility of LOCS III grading for radiation cataracts. We also showed that there was a correlation between dose to the lens and occurrence not only of posterior subcapsular cataracts subtype (P) but also of nuclear color cataracts (NC), and report that extent/severity of posterior subcapsular (P) correlated with irradiated lens volume. Better knowledge of correlations between LOCS III and lens dose-volume effects may help to personalize PBT planning, not only with current modalities of delivering PBT but possibly even more with PBT facilities using active scanning (pending some adaptations of equipment used for eye treatment). Prospective studies using the LOCS III are needed to better address the subtype and severity of cataracts in oncology, and to define thresholds for surgery. Better characterization of cataracts after irradiation might also help to further fill gaps in current knowledge of the mechanisms of radiation induced cataracts.

FIGURE CAPTIONS

Figure 1: Cataract grading according to the LOCS III at 3 years after proton beam therapy for choroidal melanoma. NO 0, NC 1, C 0, P 3. NO: nuclear opalescence, NC: nuclear color, C: cortical, P: posterior subcapsular cataracts.

Figure 2 :

 2 Figure 2: Cataract extent and anatomical location according to the LOCS III in 52 patients The X axis corresponds to the cataract score according to the LOCS III. The Y axis corresponds to the frequency of the different cataract subtypes observed in the study population. NO: nuclear opalescence, NC: nuclear color, C: cortical, P: posterior subcapsular cataracts.

ACKNOWLEDGMENTS:

a. Funding/Support: None. b. Financial disclosures: T. Mathis is a consultant for Allergan, Bayer and Novartis; L. Kodjikian is a consultant for Alcon, Alimera, Allergan, Bayer, Novartis and Théa; The following authors have no financial disclosures: L. Rosier, F. Meniai, S. Baillif, J. Herault, JP. Caujolle, J. Salleron and J. Thariat c. Other acknowledgments: The authors thank Dr Philip Robinson (Direction de la Recherche Clinique et de l'Innovation, Hospices Civils de Lyon) for proofreading and critical review of the manuscript, and Dr Arthur Handaye-Dessus for data analysis.