Mamadou B Keita

Ibrahim Hamad

Fadi Bittar
email: fadi.bittar@univ-amu.fr

Looking in apes as a source of human pathogens

Because of the close genetic relatedness between apes and humans, apes are susceptible to many human infectious agents and can serve as carriers of these pathogens. Consequently, they present a serious health hazard to humans. Moreover, many emerging infectious diseases originate in wildlife and continue to threaten human populations, especially vector-borne diseases described in great apes, such as malaria and rickettsiosis. These wild primates may be permanent reservoirs and important sources of human pathogens. In this special issue, we report that apes, including chimpanzees (Pan troglodytes), bonobos (Pan paniscus), gorillas (Gorilla gorilla and Gorilla beringei), orangutans (Pongo pygmaeus and Pongo abelii), gibbons (Hylobates spp., Hoolock spp. and Nomascus spp) and siamangs (Symphalangus syndactylus syndactylus and Symphalangus continentis), have many bacterial, viral, fungal and parasitic species that are capable of infecting humans. Serious measures should be adopted in tropical forests and sub-tropical areas where habitat overlaps are frequent to survey and prevent infectious diseases from spreading from apes to people.

Introduction

It is well known that the majority of emerging infectious diseases are of zoonotic origin and are primarily caused by wildlife-or vector-borne pathogens [START_REF] Jones | Global trends in emerging infectious diseases[END_REF]. The increased incidence of zoonoses highlights the critical need for real-time pathogen monitoring in wildlife animals, especially in at-risk regional "hotspots" where new emerging infectious diseases have been reported [START_REF] Jones | Global trends in emerging infectious diseases[END_REF].

Apes (superfamily Hominoidea) include the lesser apes, known as gibbons and siamangs, that are represented by 4 genera (Hoolock, Hylobates, Symphalangus and Nomascus) and the great apes that also contain 4 genera (Homo (humans), Pan (chimpanzees and bonobos), Gorilla (gorillas) and Pongo (orangutans)) [START_REF] Don | Mammal species of the world. A taxonomic and geographic reference[END_REF]. Because of their high genomic similarity and close evolutionary relationships to human beings, apes share many diseases with humans [START_REF] Raoult | The apes as reservoir of human pathogens[END_REF]. These shared infectious diseases may result from pathogens inherited from a common ancestor [START_REF] Davies | Phylogeny and geography predict pathogen community similarity in wild primates and humans[END_REF]. However, cross-species transmission between close relatives is also possible. Many factors can create opportunities for pathogen transmission between apes and humans, including their frequent contact during ecotourism, searching for food, research or simply sharing the same ecosystem (i.e., habitat overlap) [START_REF] Pedersen | Cross-species pathogen transmission and disease emergence in primates[END_REF]. The establishment of new infections in humans depends on both the pathogen and human biology (i.e., the capacity of pathogen to expand its host range and become a human pathogen) [START_REF] Pedersen | Cross-species pathogen transmission and disease emergence in primates[END_REF]. Ape pathogens most likely need very few changes, if any, to infect humans. Thus, the absence of appropriate and timely immune responses in the naive humans leads to the emergence and rapid spread of the infectious diseases [START_REF] Pedersen | Cross-species pathogen transmission and disease emergence in primates[END_REF].

Mathematical models showed that a high proportion of pathogens are shared between close relatives such as humans and apes [4e7]. Moreover, recent research has alerted the scientific communities to the emergence of human infections linked to African great apes [START_REF] Sharp | Evolution. Great apes and zoonoses[END_REF]. Chimpanzees were found to be the natural reservoir of the pandemic and non-pandemic human immunodeficiency virus type 1 (HIV-1) [START_REF] Keele | Chimpanzee reservoirs of pandemic and nonpandemic HIV-1[END_REF], the causative agent of acquired immune deficiency syndrome (AIDS). Moreover, a new Mycobacterium tuberculosis strain was recovered from a wild chimpanzee [START_REF] Coscolla | Novel Mycobacterium tuberculosis complex isolate from a wild chimpanzee[END_REF], and gorillas were identified as the origin of the human malaria parasite Plasmodium falciparum [START_REF] Liu | Origin of the human malaria parasite Plasmodium falciparum in gorillas[END_REF]. Rickettsia felis, an emerging vectorborne pathogen that causes rickettsioses, was documented in the feces of many species of apes, including gorillas, chimpanzees and bonobos [START_REF] Keita | Molecular evidence for the presence of Rickettsia Felis in the feces of wild-living African apes[END_REF]. It is important to note that for AIDS and malaria, African great apes have much more variety of causative related pathogens than those in humans. This difference in pathogen variety suggests that either some specific ape pathogens have not yet been able to infect and spread widely throughout the human population or that cross-infection/adaptation of these species in human beings yet to occur [START_REF] Sharp | Evolution. Great apes and zoonoses[END_REF].

1

Unfortunately, the published data regarding pathogens of the apes that live in Asia remain quite poor. Large surveillance efforts in these ape populations are required to document the potential for zoonotic diseases from this continent to spread to humans.

Although the transmission of infectious diseases between apes and humans can occur in both directions, this review focuses on the importance of apes as carriers and possible source of infective organisms that have the potential to become human pathogens.

Apes as a reservoir and source of human pathogenic bacteria

Although bacterial and rickettsial diseases represent more than half of the emerging infectious diseases worldwide [START_REF] Jones | Global trends in emerging infectious diseases[END_REF], the literature contains few reports regarding the pathogenic bacteria of apes and no report of transmission to human beings. Enteric bacterial agents such as Salmonella spp., Shigella spp., Campylobacter spp. and Escherichia coli can be carried by many species of gorillas [START_REF] Nizeyi | Campylobacteriosis, salmonellosis, and shigellosis in free-ranging human-habituated mountain gorillas of Uganda[END_REF][START_REF] Rwego | Gastrointestinal bacterial transmission among humans, mountain gorillas, and livestock in Bwindi Impenetrable National Park, Uganda[END_REF]. Feces of infected animals are the most likely primary sources of these bacteria. Nizeyi et al. reported that the prevalence of isolation for Campylobacter spp., Salmonella spp., and Shigella spp. in mountain gorillas (Gorilla gorilla beringei) from Uganda is 19%, 13%, and 6%, respectively, without enteric illness in any observed gorillas [START_REF] Nizeyi | Campylobacteriosis, salmonellosis, and shigellosis in free-ranging human-habituated mountain gorillas of Uganda[END_REF]. Salmonella species and Shigella spp. (Shigella sonnei, Shigella boydii, and Shigella flexneri) were isolated principally from subadult and adult gorillas [START_REF] Nizeyi | Campylobacteriosis, salmonellosis, and shigellosis in free-ranging human-habituated mountain gorillas of Uganda[END_REF]. However, the prevalence of these enteropathogens may have been underestimated due to the low sensitivity of the classical methods used for their detection. The molecular survey conducted recently by Whittier et al. on G. beringei using real-time PCR confirmed that the prevalence of Campylobacter spp. can reach 85% in mountain gorilla populations [START_REF] Whittier | Real-time PCR detection of Campylobacter spp. In free-ranging mountain gorillas (Gorilla beringei beringei)[END_REF].

Respiratory bacterial agents have also been recovered in wild great apes (chimpanzees and gorillas) [16e18]. Three bacteria including Pasteurella multocida, Streptococcus pneumoniae and Klebsiella pneumoniae, which are also infectious to humans, have been detected in apes that died from pneumonia. Molecular characterization of these strains indicated the presence of pathogenicity factors such as type 4 fimbriae and superoxide dismutases in P. multocida and pneumolysin in S. pneumonia that could explain their potential virulence relevance [START_REF] Kondgen | Pasteurella multocida involved in respiratory disease of wild chimpanzees[END_REF][START_REF] Chi | New Streptococcus pneumoniae clones in deceased wild chimpanzees[END_REF]. However, in most cases, a viral upper respiratory tract infection by metapneumovirus predisposed these great apes to bacterial infections [16e18].

Several emerging bacteria have been characterized and found to be infective in wild great apes; these bacteria include Bacillus anthracis [START_REF] Leendertz | A new Bacillus anthracis found in wild chimpanzees and a gorilla from West and Central Africa[END_REF] and M. tuberculosis [START_REF] Coscolla | Novel Mycobacterium tuberculosis complex isolate from a wild chimpanzee[END_REF]. First, two outbreaks of anthrax caused by a variant of B. anthracis "B. cereus var. anthracis" killed at least 6 chimpanzees in Côte d'Ivoire and 3 chimpanzees and one gorilla in Cameroon [START_REF] Leendertz | A new Bacillus anthracis found in wild chimpanzees and a gorilla from West and Central Africa[END_REF]. Moreover, a recently case of a wild chimpanzee infected with M. tuberculosis has been documented in Côte d'Ivoire [START_REF] Coscolla | Novel Mycobacterium tuberculosis complex isolate from a wild chimpanzee[END_REF]. The phylogenomic analyses demonstrated that this strain belongs to a new lineage of the M. tuberculosis complex, but it is more closely related to lineage 6 that has been described in humans and is known as Mycobacterium africanum (West Africa 2) [START_REF] Coscolla | Novel Mycobacterium tuberculosis complex isolate from a wild chimpanzee[END_REF].

Finally, R. felis, a fastidious intracellular pathogen transmitted to human by ectoparasites and the bites of infected mosquitoes, has also been detected in gorilla, chimpanzee and bonobo feces using molecular methods [START_REF] Keita | Molecular evidence for the presence of Rickettsia Felis in the feces of wild-living African apes[END_REF]. In the aforementioned study, the feces of 11% of apes living in the wild (a total of 1028 samples tested) were found to be positive for R. felis and R. felis-like organisms, thus indicating the importance of apes as potential host or reservoir for this emerging rickettsial bacterium in sub-Saharan Africa where its infection is a common public health problem [START_REF] Keita | Molecular evidence for the presence of Rickettsia Felis in the feces of wild-living African apes[END_REF].

Apes as a reservoir and source of human pathogenic viruses

There have been various studies demonstrating that apes, especially African great apes, constitute a potential reservoir and source of numerous human pathogenic viruses [START_REF] Calvignac-Spencer | Wild great apes as sentinels and sources of infectious disease[END_REF] (Fig. 1). Most species of apes, if not all, can carry retroviruses (family Retroviridae) including simian immunodeficiency viruses (SIVs), simian T-cell lymphotropic viruses (STLVs) and simian foamy viruses (SFVs). Thus, considerable research has been conducted to understand the prevalence, genetic diversity, geographic distribution and transmission of these viruses in ape populations [START_REF] Peeters | Simian retroviruses in African apes[END_REF][START_REF] Sharp | Origins of HIV and the AIDS pandemic[END_REF]. It is now well established that the human immunodeficiency viruses HIV-1 groups M and N are very closely related to SIVcpzPtt of chimpanzees (Pan troglodytes troglodytes) and thus are of chimpanzee origin, while HIV-1 group P is of western gorilla (Gorilla gorilla gorilla) origin [START_REF] Sharp | Origins of HIV and the AIDS pandemic[END_REF]. Despite numerous interspecies transfers of the retrovirus from apes to human, only HIV-1 group M originated from chimpanzees in Cameroon and subsequently spread worldwide to become responsible for the pandemic form of AIDS in humans [START_REF] Keele | Chimpanzee reservoirs of pandemic and nonpandemic HIV-1[END_REF][START_REF] Peeters | Simian retroviruses in African apes[END_REF][START_REF] Sharp | Origins of HIV and the AIDS pandemic[END_REF]. Currently, no evidence has been found of SIV infections in Asian apes (orangutans and gibbons) [START_REF] Ayouba | Nonhuman primate retroviruses from Cambodia: high simian foamy virus prevalence, identification of divergent STLV-1 strains and no evidence of SIV infection[END_REF]. In contrast to SIVs that are present principally in African gorillas and chimpanzees, STLVs are also retroviruses but are widely distributed among African and Asian apes including gorillas, chimpanzees, orangutans and gibbons [START_REF] Ayouba | Nonhuman primate retroviruses from Cambodia: high simian foamy virus prevalence, identification of divergent STLV-1 strains and no evidence of SIV infection[END_REF][START_REF] Nerrienet | Simian T cell leukaemia virus type I subtype B in a wild-caught gorilla (Gorilla gorilla gorilla) and chimpanzee (Pan troglodytes vellerosus) from Cameroon[END_REF]. In the early 2000s, a serological survey followed by molecular confirmation indicated that a wild-caught gorilla and a wild-caught chimpanzee were infected with STLV-1 strains that were closely related to HTLV-1 strains present in human inhabitants of the same region (south Cameroon); this suggests the possible transmission of STLV-1 to humans from African apes [START_REF] Nerrienet | Simian T cell leukaemia virus type I subtype B in a wild-caught gorilla (Gorilla gorilla gorilla) and chimpanzee (Pan troglodytes vellerosus) from Cameroon[END_REF]. More recently, phylogenetic studies confirmed this conclusion and showed that STLVs cluster according to geographical origin rather than by host species, leading to the hypothesis that many interspecies transmissions have occurred between primates, including those from apes to humans [START_REF] Peeters | Simian retroviruses in African apes[END_REF][START_REF] Ayouba | Nonhuman primate retroviruses from Cambodia: high simian foamy virus prevalence, identification of divergent STLV-1 strains and no evidence of SIV infection[END_REF].

Ebola virus belongs to the Filoviridae family and is a highly virulent virus of humans and nonhuman primates that causes severe hemorrhagic fever and death within few days. This virus has been responsible for outbreaks in several countries of Sub-Saharan Africa, such as the Democratic Republic of Congo, Gabon, Sudan, Ivory Coast, Uganda and, most recently, Guinea [START_REF] Leroy | Ebola and Marburg hemorrhagic fever viruses: major scientific advances, but a relatively minor public health threat for Africa[END_REF][START_REF] Baize | Emergence of Zaire ebola virus disease in Guinea -preliminary report[END_REF]. Although bats are considered the natural hosts of filoviruses, Ebola virus transmission to humans appear to be linked to direct contact with live or dead apes. Hunters that come into contact with the infected gorilla and chimpanzee carcasses are especially at risk of contracting the disease [START_REF] Leroy | Ebola and Marburg hemorrhagic fever viruses: major scientific advances, but a relatively minor public health threat for Africa[END_REF]. Recent surveillance of Asian apes in Indonesia for filoviruses showed that 18.4% of healthy orangutans (Pongo pygmaeus) are seropositive for the Ebola virus. This high seroprevalence in asymptomatic orangutans suggests that this ape may serve as carrier or host and thus could present a potential risk for humans living in this region of Asia [START_REF] Nidom | Serological evidence of ebola virus infection in indonesian orangutans[END_REF].

The hepatitis B virus (family Hepadnaviridae) has also been characterized in apes from both Africa and Asia at high frequencies comparable to those obtained from humans in endemic zones [START_REF] Lyons | Species association of hepatitis B virus (HBV) in non-human apes; evidence for recombination between gorilla and chimpanzee variants[END_REF]. The presence of cross-species transmission and/or recombination between human and ape hepatitis B virus variants [START_REF] Lyons | Species association of hepatitis B virus (HBV) in non-human apes; evidence for recombination between gorilla and chimpanzee variants[END_REF] and the close genomic similarity of human and ape hepatitis B viruses [START_REF] Sa-Nguanmoo | Hepatitis B virus infection in non-human primates[END_REF] calls for extensive phylogenetic investigations to understand the diversity, the evolution and the worldwide spread of this virus.

Other pathogenic viruses, including adenoviruses [START_REF] Wevers | Novel adenoviruses in wild primates: a high level of genetic diversity and evidence of zoonotic transmissions[END_REF] (family Adenoviridae), Lymphocryptovirus [START_REF] Ehlers | Lymphocryptovirus phylogeny and the origins of Epstein-Barr virus[END_REF] and cytomegaloviruses [START_REF] Leendertz | Novel cytomegaloviruses in free-ranging and captive great apes: phylogenetic evidence for bidirectional horizontal transmission[END_REF] (family Herpesviridae), metapneumoviruses [START_REF] Kondgen | Pasteurella multocida involved in respiratory disease of wild chimpanzees[END_REF][START_REF] Chi | New Streptococcus pneumoniae clones in deceased wild chimpanzees[END_REF][START_REF] Palacios | Human metapneumovirus infection in wild mountain gorillas, Rwanda[END_REF] (family Paramyxoviridae), polyomaviruses [START_REF] Leendertz | African great apes are naturally infected with polyomaviruses closely related to Merkel cell polyomavirus[END_REF] (family Polyomaviridae) and enteroviruses [START_REF] Harvala | Co-circulation of enteroviruses between apes and humans[END_REF] (family Picornaviridae), are not exclusively human-specific and have also been detected in apes. Moreover, based on phylogenetic analyses, some of these viruses variants found in apes are remarkably closely related to human viruses, indicating the zoonotic potential of primate viruses to spread horizontally into the local human populations [30e34].

Apes as a reservoir and source of human parasites

Parasitological studies from different free-ranging and captive apes have revealed a multitude of parasite species ranging from single-celled protozoa to multicellular helminths [START_REF] Toft | The pathoparasitology of the alimentary tract and pancreas of nonhuman primates: a review[END_REF] (Fig. 2). The high load of these parasites in the various ape hosts may render these animals potential zoonotic reservoirs that could be responsible for an emerging parasitic zoonosis [START_REF] Calvignac-Spencer | Wild great apes as sentinels and sources of infectious disease[END_REF].

Ape parasites can be transmitted to humans through vectormediated transmission (usually arthropods) via fecal-oral transmission or through direct or prolonged contact with apes [START_REF] Calvignac-Spencer | Wild great apes as sentinels and sources of infectious disease[END_REF]. Although little published data has demonstrated the direct transmission of parasites from apes to human, a number of zoonotic diseases have been reported, providing evidence of shared susceptibility of both apes and human to same pathogens [START_REF] Homsy | Ape Tourism & Human Diseases: How Close Should We Get? a Critical Review of the Rules and Regulations Governing Park Management &Tourism for the Wild Mountain Gorilla[END_REF]. The transmission of these pathogens among primates in the wild may have negative consequences for public health and wildlife conservation management programs [START_REF] Mountain | Risk of disease transmission between conservation personnel and the mountain gorillas: results from an employee health program in Rwanda[END_REF].

Apes as reservoir for human parasitic protozoa

Regarding unicellular eukaryotic organisms, apes exhibit several blood/tissue and intestinal protozoa that can cause diseases of concern for human beings (Fig. 2). Members of the blood and tissue apicomplexan parasites of the genus Plasmodium have been described in gorillas, chimpanzees and bonobos [11,38e41]. Indeed, very recent data provided definitive evidence that the most virulent human malaria parasite (P. falciparum) originated from gorillas [START_REF] Liu | Origin of the human malaria parasite Plasmodium falciparum in gorillas[END_REF]. In addition to the occurrence of Plasmodium species that cause malaria (P. falciparum, Plasmodium vivax, Plasmodium malariae, Plasmodium ovale) in a wide range of apes, other members of the genus Plasmodium have also been reported to cause natural infections in apes (Fig. 2).

Furthermore, kinetoplastid protozoans, such as species of Trypanosoma, have been reported in gorillas, chimpanzees and orangutans [START_REF] Baker | Protozoa of Tissues and Blood (Other than the Haemosporina)[END_REF][START_REF] Hoare | The Trypanosomes of Mammals[END_REF], and the first natural infection cases of the hemoflagellate protozoan Trypanosoma cruzi, the causative agent of human Chagas disease, have been reported in chimpanzees and gibbons [START_REF] Bommineni | Fatal acute Chagas disease in a chimpanzee[END_REF][START_REF] Dorn | Low prevalence of Chagas parasite infection in a nonhuman primate colony in Louisiana[END_REF]. Although the transmission of this parasite requires a blood-sucking triatomine insect, direct transmission could also occur among the infected captive animals and their zookeepers [START_REF] Dorn | Low prevalence of Chagas parasite infection in a nonhuman primate colony in Louisiana[END_REF].

The free-living amoeba Balamuthia mandrillaris, the etiological agent of human granulomatous amoebic encephalitis, has been identified in brain tissue from both gorillas and gibbons [START_REF] Rideout | Fatal infections with Balamuthia mandrillaris (a free-living amoeba) in gorillas and other old world primates[END_REF]. Although B. mandrillaris is regarded as an emergent threat to humans, the transmission of this pathogen from apes to human is rarely recorded. However, close contact between humans and infected non-human primates might increase the risk of transmission [START_REF] Rideout | Fatal infections with Balamuthia mandrillaris (a free-living amoeba) in gorillas and other old world primates[END_REF].

The gastrointestinal walls of apes are colonized by parasitic protozoan, and fecal-based studies of wild populations of gorillas, chimpanzees and orangutans revealed the presence of certain intestinal human parasites such as Entamoeba histolytica [START_REF] Cooper | Phylogenetic host specificity and understanding parasite sharing in primates[END_REF], Giardia duodenalis [START_REF] Cooper | Phylogenetic host specificity and understanding parasite sharing in primates[END_REF][START_REF] Huffman | Seasonal trends in intestinal nematode infection and medicinal plant use among chimpanzees in the mahale mountains, Tanzania[END_REF] and Cryptosporidium species [START_REF] Gillespie | A legacy of low-impact logging does not elevate prevalence of potentially pathogenic protozoa in free-ranging gorillas and chimpanzees in the Republic of Congo: logging and parasitism in African apes[END_REF] in the guts of these animals. Moreover, common human subtypes of Blastocystis sp. that are often associated with chronic infections have also been identified in the digestive tracts of both captive and free-living apes including gorillas, chimpanzees, bonobos, gibbons and orangutans [START_REF] Alfellani | Diversity and distribution of Blastocystis sp. subtypes in non-human primates[END_REF]. Furthermore, the ciliated parasite Balantidium coli that cause human balantidiasis has also been detected in the stools of a wide range of gorilla, chimpanzee and orangutan populations [START_REF] Cooper | Phylogenetic host specificity and understanding parasite sharing in primates[END_REF]. The major source of infection with these enteric parasites is through the fecal-oral route [START_REF] Thompson | Zoonotic enteric protozoa[END_REF]. Although there is less opportunity for the feces of wild apes to contaminate human water supplies, transmission is still possible, especially for people who are involved in caring for captive apes [START_REF] Schuster | Amebae and ciliated protozoa as causal agents of waterborne zoonotic disease[END_REF].

Apes as a reservoir of human helminths

Coprological studies revealed the presence of a variety of intestinal nematodes among gorilla, chimpanzee and orangutan populations (Fig. 2). For example, the common human enteric round worm Ascaris lumbricoides, the whipworm Trichuris trichiura and species of the pinworm Enterobius have been found in the gastrointestinal tracts of almost all of the great apes [START_REF] Cooper | Phylogenetic host specificity and understanding parasite sharing in primates[END_REF]. In addition, species of Oesophagostomum and Strongyloides, nematodes that cause oesophagostomosis and strongyloidiasis, respectively, have also been detected in the guts of African great apes [START_REF] Cooper | Phylogenetic host specificity and understanding parasite sharing in primates[END_REF][START_REF] Krief | Clinical and pathologic manifestation of oesophagostomosis in African great apes: does self-medication in wild apes influence disease progression?[END_REF]. Some reports described human infections with species of Oesophagostomum in northern Togo and Ghana, particularly in regions where apes live in close proximity to humans [START_REF] Guillot | Nematodes of the genus Oesophagostomum: an emerging risk for humans and apes in Africa?[END_REF]. The digestive tracts of apes such as gorillas and chimpanzees can also be infected with the zoonotic parasite for Necator americanus, the hookworm that causes human hookworm. Molecular evidence revealed the possibility of cross-infection with Necator hookworms in humans and great apes that co-exist in the same area [START_REF] Hasegawa | Humans and great apes cohabiting the forest ecosystem in central african republic harbour the same hookworms[END_REF].

In addition to enteric nematodes, the great apes are also susceptible to a variety of filarial nematodes including Onchocerca volvulus, a nematode that causes human onchocerciasis in Africa and has been observed in gorillas, Dirofilaria immitis, a nematode that is responsible for severe human heart problems and has been detected in orangutans, and Loa loa, the etiological agent of human loaiasis that has also been reported in gorillas and chimpanzees [START_REF] Toft | Parasitic diseases[END_REF].

Little information regarding the diversity and transmission of cestodes and trematodes between humans and apes is available. The only cestode that is considered to be a potential zoonosis from apes is Hymenolepsis nana, for which chimpanzees might serve as reservoir host [START_REF] Mbaya | Gastrointestinal parasites of captive and freeroaming primates at the afi mountain primate conservation area in Calabar, Nigeria and their zoonotic implications[END_REF]. Regarding the parasitic trematodes, the blood flukes Schistosoma mansoni and Schistosoma haematobium, the causative agents of schistosomiasis, have been observed in chimpanzees [START_REF] Mbaya | Gastrointestinal parasites of captive and freeroaming primates at the afi mountain primate conservation area in Calabar, Nigeria and their zoonotic implications[END_REF][START_REF] Taylor | A case of natural infection of S. haematobium in a Senegalese baboon (Papio sp.)[END_REF].

Apes as reservoir for human pathogenic fungi

Little data exists concerning the occurrence and diversity of fungi in great apes. However, the primary zoonotic fungal diseases of concern for humans belong to group of microsporidia, and intracellular parasitic species belonging to the genera Enterocytozoon and Encephalitozoon have been reported in multiple species of apes [START_REF] Sak | Diversity of microsporidia (Fungi: microsporidia) among captive great apes in European zoos and African sanctuaries: evidence for zoonotic transmission?[END_REF], as shown in Fig. 2. The transmission mode of these intracellular parasites remains unclear, but it is thought that close contact between apes and humans increases the risk of transmission of these infectious diseases [START_REF] Sak | Diversity of microsporidia (Fungi: microsporidia) among captive great apes in European zoos and African sanctuaries: evidence for zoonotic transmission?[END_REF].

Apes as reservoir for arthropods causing human disease

In addition to their role as vectors of many severe parasitic diseases, arthropods such as fleas, lice, ticks, and mites also serve as intermediate biological hosts for a variety of infectious disease agents (Fig. 2). Tunga penetrans is a parasitic flea that cause human tungiasis and has been confirmed to use different primates as reservoirs [START_REF] Toft | Parasitic diseases[END_REF]. T. penetrans has been observed infecting the skin of gorillas. The risk of transmission of this arthropod to humans increases in cases of direct contact, particularly in endemic areas [START_REF] Toft | Parasitic diseases[END_REF].

The most prevalent sucking lice species that colonize humans are Pthirus pubis and Pediculus humanus capitis. These species have also been reported to be associated with apes, and evidence suggests that these parasites may be able to switch between human and ape hosts [START_REF] Toft | Parasitic diseases[END_REF]. Interestingly, apes such as gorillas can also be parasitized by Pthirus gorilla, a louse that is phylogenetically a very close relative of the human parasite P. pubis and is regarded as a common pubic louse. It is assumed that our human ancestors contracted P. gorilla millions years ago by either living in close proximity to gorillas or using their bedding sites [START_REF] Reed | Pair of lice lost or parasites regained: the evolutionary history of anthropoid primate lice[END_REF]. Finally, different species of mites belonging to the genus Sarcoptes have been documented to invade a wide range of ape hosts. The itch mite Sarcoptes scabiei is the causative agent of human scabies and has observed to also infest the skin of gorillas. The possibility of transmission of S. scabiei to humans increased when they came into close contact with infested animals [START_REF] Toft | Parasitic diseases[END_REF].

Conclusion

The identification of natural or wild sources for pathogens is necessary to avoid the emergence or reemergence of infectious diseases. Apes, our closest relatives, deserve special attention because they constitute serious reservoir of many micro-and macro-pathogens for humans including viruses, bacteria, parasitic helminths and protozoans. Thus, people living close to or in direct contact with apes are at risk for inter-species transmission and infection. Non-invasive methods showed these potential interactions could be involved in many emerging infectious diseases such as HIV and malaria. However, many additional efforts are essential to detect anthropozoonoses from wild apes and to prevent transmission to humans. Future investigation of pathogens in Asian apes is required, and the large-scale monitoring of bacterial and fungal species in ape populations is needed to gain global insights into the emerging zoonotic events from wildlife.

Fig. 1 .

 1 Fig. 1. Apes (chimpanzees, gibbons, gorillas and orangutans) serving as viral reservoirs. Viral genera and species are distributed into the following nine families: Retroviridae (dark red), Herpesviridae (green), Hepadnaviridae (orange), Adenoviridae (purple), Papillomaviridae (blue), Filoviridae (light blue), Picornaviridae (black), Paramyxoviridae (red) and Polyomaviridae (light green). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 2 .

 2 Fig. 2. Parasitic reservoir of apes (chimpanzees, gibbons, gorillas and orangutans). Helminths (black), Protozoa (blue), Fungi (green) and Arthropods (pink). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Acknowledgments

Fadi Bittar was supported by a Chair of Excellence IRD provided by the Institut de Recherche pour le D eveloppement/IHU M editerran ee Infection.


Mathias Rapacioli
email: mathias.rapacioli@irsamc.ups-tlse.fr

Johann Christian Schön

Nathalie Tarrat
email: nathalie.tarrat@cemes.fr

Nathalie Tarrat Cemes

Exploring energy landscapes at the DFTB quantum level using the threshold algorithm : the case of the anionic metal cluster Au - 20

Keywords: Gold Clusters, Threshold algorithm, DFTB, Energy landscape, Probability Flows, Disconnectivity

We report the combination of the threshold algorithm with the Density Functional based Tight Binding method (DFTB) allowing for the exploration of complex potential energy surfaces and the evaluation of probability flows between their regions, at the quantum level. This original scheme is used to explore the energy landscape of an anionic 20-atom gold cluster, Au - 20 . On the basis of the relevant structures, 19 structural groups are highlighted, all of them being variations about the pyramidal shape : (i) distorted pyramids, (ii) pyramids in which the atom of one of the facets has been removed, leaving a hole, and placed at different positions on the cluster and (iii) pyramids on which an atom located at a vertex has been removed and placed on an edge or on a facet. Upper limits of the energies required to connect the basins of the 19 groups on the potential energy surface are evaluated. Moreover, the attractive basins are identified on the basis of the analysis of the probability flows on the landscape. The comparison of the disconnectivity tree with the results of the flux analysis provides a consistent representation of the Au - 20 basins' proximity. Finally, we show how the new scheme allowed for the identification of counter-intuitive transition pathways.

Introduction

Over the past decades, complex energy landscapes that exhibit multitudes of local minima and a broad range of energy barriers have left the realm of mathematics and optimization theory, [1][2][3][START_REF] Salamon | Facts, Conjectures, and Improvements for Simulated Annealing[END_REF] where they are often known as cost functions, to become an indispensable playground and tool for investigations of biological, chemical and physical systems, [START_REF] Wales | Energy Landscapes with Applications to Clusters, Biomolecules and Glasses[END_REF] ranging from studies of structural glasses [START_REF] Stillinger | [END_REF][7][8][9][10] and spin glasses, [11][12][13] and inverse problems, over macromolecules such as proteins, [14,15] peptides, [16][17][18][19] glycans, [20,21] and clusters [START_REF] Wales | Advances in Chemical Physics[END_REF][START_REF] Ferrando | [END_REF][24] to crystalline compounds [25,26] and questions of evolution. [27][28][29] Energy landscapes are used to describe and visualize the state space of such systems, and the analysis of their barrier structure provides insight into their dynamics on short and long time scales. Regions of the landscape of chemical systems, which are locally ergodic on given observational time scales, [START_REF] Schön | Proceedings of RIGI-workshop 1998[END_REF][START_REF] Schön | [END_REF][32] correspond to metastable compounds or conformations, and the properties of the transition regions connecting these locally ergodic regions control both the life-times of the various modifications and the transformation pathways between them. Quite frequently, such landscapes exhibit a hierarchy of time scales, and a complicated barrier structure, making brute force simulations of their time evolution infeasible.

A multitude of algorithmic tools, especially global optimization algorithms, [11,[START_REF] Holland | Adaptation in Natural and Artificial Systems[END_REF][START_REF] Deaven | [END_REF][35][36] have been developed to determine the local minima that are typically at the heart of the locally ergodic regions. Similarly, a variety of methods have been deployed to identify individual saddle points and pathways between given pairs of local minima. [37][38][39][40] Finally, simulations of the dynamics on complex energy landscapes have required the development of new approaches that are usually based on combinations of molecular dynamics or Monte Carlo algorithms with heuristic or systematic tools. [41][42][43][44][45][START_REF] Laio | Proc. Nat. Acad. Sci[END_REF] Here, the goal is to overcome the issue of multiple time scales separated by orders of magnitude in a physically and chemically intuitive fashion, while remaining as systematical and unbiased as possible.

A major problem is the fact that fast, ie. computationally affordable, crossings of energy barriers of a certain height between two relatively close-by minima but without already prescribing a path to follow, typically require adding more energy to the system in some fashion -usually in form of temperature -than is appropriate for the phenomenon of interest. In particular, due to the complexity of the multi-minima landscape, high temperatures allow the system to range widely over the landscape moving towards many other neighbor minima instead of the "target" local minimum. Similarly, in a high-dimensional space, it becomes rather difficult to even find the exit from (or entrance to) a given minimum since the walker representing the system will spend much of the time just searching for this typically very small exit region connecting the basin to the rest of the energy landscape. This multitude of available pathways, with the resulting difficulty of the system to pick a particular one, is an example of the second class of barriers, which are prominent on a complex energy landscape: the so-called entropic barrier. [32,[START_REF] Schön | [END_REF]48] Typically, the importance of such barriers for the dynamics rapidly increases with size of the system; often they are actually more relevant than the existing lowest energy barriers regarding the time scales on which a metastable system with many degrees of freedom evolves. However, most standard exploration algorithms either ignore entropic barriers or provide no way to measure them in a systematic fashion.

One class of approaches that systematically determine such entropic barriers are the so-called lid or threshold algorithms, [3,13,32,[49][50][51] where increasingly large pockets of the energy landscape that are accessible below a sequence of energy lids or thresholds are systematically explored and the probability flows between the regions that are connected below a given lid are measured as function of threshold energy. [52,53] Typically, one speaks of a lid algorithm, if the under-lying state space is discrete, e.g. for a spin glass [13] or a combinatorial optimization problem [3], and of the threshold algorithm if the state space is continuous, e.g. in chemical systems. [49,50] The great advantage of measuring such probability flows as function of threshold energy is the fact that we can separate the entropic and the energetic aspects of the barrier structure of the landscape. [32,52,53] Furthermore, starting from e.g. a low-energy local minimum, this approach yields an overview over the neighboring minima on the energy landscape, and identifies the energetic and entropic barriers separating them. Repeating this lid based exploration from the newly discovered minima, it becomes possible to map the whole landscape in a mosaic fashion, and to reconstruct both the energy barrier and entropic barrier based connectivity of the landscape.

Since unbiased explorations of energy landscapes always require very large numbers of energy evaluations, any application of such an algorithm runs into feasibility problems for systems with expensive energy calculations such as chemical compounds. Dealing with this issue by employing e.g. empirical potentials instead of ab initio energy calculations can lead to more or less grave inaccuracies, especially if the empirical potentials are fitted to only a few local minima but do not yield a faithful representation of the whole landscape. As a consequence, the minima found on the empirical landscape may be different from those on the ab initio landscape -both with regard to their existence and their relative energies. [53,54] Furthermore, the energetic barriers between the minima will more or less strongly depend on the energy function, and similarly the entropic barriers may also differ as a consequence.

While there is no perfect solution to this conundrum, one promising compromise for chemical systems is to employ approximated ab initio energies, such that we expect that essentially all local minima of the "true" ab initio landscape will exist on the simplified landscape, that their relative energies are realistic, and that also the energy barriers will not differ too much from the "true" ones. One very promising approach is to employ the so-called Density Functional based Tight Binding (DFTB) method, which has proven to be quite successful in modeling many types of chemical systems and nanoclusters. [55][56][57] In the present work, we report the incorporation of the threshold algorithm into the DFTB code deMonNano [START_REF] Heine | deMon-Nano[END_REF].

This threshold/DFTB scheme is then used to investigate the energy landscape of gold clusters. Such clusters have attracted much interest since the 1980s because of their remarkable properties in various fields such as medicine [START_REF] Dykman | [END_REF], catalysis [START_REF] Hutchings | Metal Nanoparticles and Nanoalloys[END_REF], nano-electronics [61] and nano-optics [62]. Among the vast literature focused on gold clusters , numerous works are devoted to Au 20 [63,64,66,73,74,80,88,99,107] because this cluster presents a double magic number: its atomic structure is a highly symmetrical pyramid and, in the simple spherical Jellium model, its 20-electron outer electronic shell is closed (1s 2 1p 6 1d 10 2s 2 superorbital configuration). In recent studies, employing a new adaptation of DFTB parameters [109,111,112], we have investigated the potential energy surface (PES) of Au (0,+,-) 20 by combining a Parallel Tempering Molecular Dynamics (PTMD) exploration [113] with periodic quenching to obtain isomers and compute their structural excitation and vibrational spectra [114][115][116]. We have observed that the Au (0,+,-) 20 lowest energy isomers exhibit pyramidal shapes, highly symmetric (T d ) for the neutral one and with very small Jahn-Teller deformations from the T d symmetry for the ions [114][115][116]. These findings are in agreement with the literature, both experimental (IR [63], Trapped Ion Electron Diffraction [117], ion mobility[118] and atomic imaging [119]) and theoretical [63,120]. Our work has shown that the structural excitation spectra of Au (0,+,-) 20 exhibit a difference in the first isomerization energy gap, which is larger for the neutral cluster than for the ions.

In the case of Au - 20 , all the identified isomers with energies below 0.45 eV above the pyramidal global minimum energy exhibit noticeable distinctive variations around the pyramidal shape, making this cluster a very suitable system to unravel the possible paths between isomers, and between groups thereof, on the PES with the help of the threshold algorithm. Beyond highlighting the connected isomer basins, we will be able to measure the probability flows between them and determine the ranges of energy where they become connected, and furthermore allow the identification of attractive basins.

In the first part of the paper, computational details are given concerning the DFTB potential used, the threshold algorithm, and the specificity of its application to the study of the Au - 20 cluster. In the second part, the zoology of the relevant isomers is presented. Their connectivity as function of the system's energy, their proximity on the PES, and the dynamical evolution (probability flows and transition pathways) between them are discussed. Finally, a conclusion and perspectives are given.

Methods

The DFTB potential

In the present work, we have used the DFTB scheme [121,122] in its second order formulation (also known as Self-Consistent Charge, SCC-DFTB [123]). With respect to DFT, the three main approximations of this method are that i/ the Kohn-Sham orbitals are expanded on a set of minimal atom-centered bases, ii/ the three-center integrals are neglected and iii/ the DFT energy is expanded in a Taylor series up to the second order around a reference density. In practice, the non-diagonal elements of the overlap and Hamiltonian matrices are tabulated from DFT calculations and expressed as functions of interatomic distances (the diagonal elements of the Hamiltonian matrix being the orbital energies of the isolated atoms) and the diatomic repulsive atomic pairwise contributions are fitted to minimize the difference to reference calculations.

The DFTB parameters used were adapted[112, 116, 124] from those reported by Fihey et al. [111] (the "auorg" set from the www.dftb.org website). The modification consisted in a shift of the p orbital energy [112].

In an earlier study, we have shown that these modified Au parameters satisfactorily reproduce the properties of systems ranging from clusters (2D/3D transition, dependency upon charge state) to bulk (lattice parameter, binding energies, elastic constants) [112]. Moreover, in the medium-size regime we are currently interested in, the structure and energetic ordering of the low-energy isomers are in agreement with the experimental and DFT data reported in the literature [112,114,125]. The performance of these parameters with respect to the modelling of medium-sized aggregates opens the way to the possibility of carrying out a global exploration of the PES of such aggregates with an approach providing an explicit description of the electronic structure.

For the single point energy calculations, we have used a criterion of 10 -8 on the atomic charges for the SCC convergence.

The threshold energy method

The threshold algorithm is employed to systematically explore many low-energy pockets of the energy landscape of a given system. [32,49,50] A pocket is defined as the region of the state space, which is accessible from a given starting point, usually a local minimum, below a given energy lid or threshold.[126] The exploration of the pocket typically takes place via many Monte Carlo random walks starting from the same minimum, but can also be performed using molecular dynamics or combinations thereof. [32,51] This ensemble of random walkers starting from the same point represents a unit of probability that has been placed into the starting minimum. Keeping track of this ensemble of walkers then corresponds to measuring the flow of probability on the energy landscape as function of threshold energy.

A crucial element is that each random step from point i to point i+1 is always accepted as long as the energy of state i+1 remains below the given energy lid, while any step above the lid is always rejected.

Periodically, every N stop random moves, we perform a set of many stochastic quenches, i.e. random walks where only states i+1 with lower or equal energy than the current state i are accepted. Each stochastic quench is followed by a local optimization. From these sets of optimized structures, we can deduce the probability flows in the pocket between the starting minimum and the other minima inside the pocket as function of energy lid and length of threshold run. One should note that due to the rapid increase in the number of states with energy on complex energy landscapes, a large fraction of the stopping points will be close to the energy threshold. Thus, the probability flows directly reflect the entropic barriers inside the pocket for a given energy interval close to the lid. In practice, we define the probability flow p i→j from isomer i to isomer j as follows: For all the N tot i threshold simulations starting from an isomer i, we define N j i as the number of final structures (after conjugate gradient optimization) corresponding to a basin j. p i→j is then defined as N j i /N tot i . This procedure is repeated for a sequence of energy lids for the same starting minimum, and subsequently for (ideally all) other local minima on the energy landscape, where not only the original set of starting minima -which had been obtained from e.g. a global optimization -but also the local minima discovered during the threshold runs are included. Thus, we obtain local densities of states as function of lid and starting local minima, and probability flows as function of energy lid and starting minima.

Furthermore, we can employ the probability flows to deduce a tree graph representation of the energy landscape, where we connect any two minima at the energy, for which there had first been an uninterrupted path feasible between these minima regardless of how far away they are on the landscape. [3,50,52,53] We note that this path may well consist of many individual pieces, each connecting two close-by local minima, since for large energy landscapes the number of steps in a given threshold run will often be very small compared to the total accessible state space volume below the lid, and thus two minima that are very far from each other but still connected below the lid are unlikely to be reached during a single individual threshold run.

Application to Au - 20

For the moveclass during the threshold runs, we selected individual atom displacements. We have inves-tigated five different lid energies (Lid1-5), corresponding to 0.01/0.02/0.03/0.04/0.05 Hartree above the energy of the global minimum configuration. For each minimum chosen as starting point and below each energy lid, at least 30 different threshold runs, i.e. random walks below the lid energy, were performed. Along each threshold run we stopped 75 times, and performed 4 quenches at each stopping point. Each piece of the threshold run between two stopping points consisted of 5000 MC steps, and each of the 4 quenches consisted of 500 MC steps followed by a conjugated gradient optimization. We have used a criterion of 4•10 -6 a.u. for the maximum atomic force to stop the local optimization.

In order to classify and compare the structures, we have used as a first criterion the energy differences. Two structures are considered as similar if their energy difference is below 10 -9 Hartree. In addition, we employed a structural similarity criterion, namely the interatomic distance-based similarity function introduced by Joswig et al. [127]. Two structures are assumed to be similar if this criterion is higher than 0.98. Note that, in our approach, mirror symmetric images are considered to belong to the same basin.

Results

Isomer analysis

The simulation protocol was initiated using as starting structures the 10 isomers reported as the lowest energy ones in the references [115,116]. Additional isomers identified during an iteration of the DFTB/threshold scheme were added to the list of starting structures if they met one of the two following criteria: i/ a total energy differing from the one of the pyramid, assumed to be the global minimum, by less than 0.45 eV or ii/ that a given minimum j represents more than 10% of the optimized structures issued from a given starting configuration i at a given lid (p i→j > 10%). This procedure has been iterated until there was no longer a new structure that meets these criteria. The total number of minima that have been identified is 736. These isomers are labelled by a number y according to the increasing energetic order. Among them, 40 isomers have been used as starting structures (45 structures met the criteria given above, but 5 were removed because they corresponded to very small structural deformations of isomers already included in the list of starting structures). These 40 structures can therefore be considered as corresponding to key basins on the potential energy surface because of their low energy and/or their high probability of being visited. In the following, these 40 starting structures will be referred as "key isomers". The structural excitation energy of these 40 key isomers and of all the minima, with respect to the pyramid, are represented in figure 1 (blue and black spectra, respectively). This structural excitation spectrum is discrete up to about 0.4 eV, at which point it begins to take on a continuous aspect. The first four isomers (y = 1,2,3,4) are slightly distorted pyramids, the isomerization gap between these pyramid-like structures and the higher energy isomers being about 0.24 eV, which is consistent with our previous work [116].

The 40 key isomers have been classified into 19 structural groups by eye. The structure of the lowest energy isomer of each group is shown in figure 2, and the corresponding structural excitation energies appear in figure 1 (red spectrum). These structures will be denoted Gx-y, x being the identifier of the structural group, y being the isomer number. The first two groups, G1 and G2, correspond to pyramid-like structures, G1 containing very slightly deformed pyramids, G2 comprising a pyramid-like structure but with one of its facets being convex. At higher energies, there are three groups containing overall pyramid-like shapes, but with noticeable distortions, either on part of the structure (G6) or on the whole (G9 and G16). In seven groups, the structures can be described as a pyramid where the atom of one of the facets has been removed, leaving a hole, and placed either on the same facet (G3), or at different positions on another facet (G5, G13 and G18), or on an edge (G10 and G15). The seventh group of this type is G19 which, although very distorted, also exhibits this type of structure. The other structural groups are based on a pyramid on which an atom located at a vertex has been removed and placed either on an edge (G4, G12, G14) or on a facet (G7, G8, G11, G17). Interestingly, the 19 structural groups described above are reminiscent of the structural classification re-ported for low-lying isomers of neutral Au 20 by Aprà et al.

[107], namely Td followed by either defective Td or compact forms.

Disconnectivity analysis

A tree graph is presented in figure 3 (tree graphs are also sometimes called disconnectivity graphs [128], disconnectivity diagrams[129] or one-dimensional projections [130]). On this graph, the energy used to place each group corresponds to that of its lowest energy isomer, the blue dashed lines show the threshold energies at which the explorations were carried out (Lid1 to Lid5), and the red lines show which groups are connected at a given lid energy. Note that these lids correspond to upper limits of the energies required to connect the groups.

Below Lid1, only the first two groups (G1 and G2) exist and there is a path connecting them. For all other groups, the energy of their lowest energy isomer is located between Lid1 and Lid2, except for group G19. In this case it is almost equal to Lid2. Between Lid1 and Lid2, there are paths to connect groups G1, G2, G4, G6 and G9. All these groups present variations around the pyramid, either a vertex atom that shifts slightly to bridge a single edge, or global deformations. Groups G5 and G18, which are very close structurally, are also connected below Lid2. At Lid3, the set containing G1, G2, G4, G6 and G9 is extended to include G7 and G16. This union of groups seems intuitive because of the compact pyramidal base of the latter (note that, at this lid, G16 is divided into two distinct subgroups, both of them linked to the set containing G1). Moreover, group G15 becomes accessible from the set containing G5+G18, these three groups having a common pattern, namely a pyramid with a hole on one facet. In addition, three new sets of groups appear at Lid3. The basins G10 and G13 are connected, the latter exhibiting a hole and differing only by the position of the adatom at the center of a triangle of a facet or on the edge of such a triangle. In a similar way, basins G8 and G12 are connected, the difference being that the adatom in this case does not come from a hole created in the middle of a facet but from a vertex. The last set that appears at Lid3 contains the groups G11, G14 and G17. They are also based on a pyramid from which one vertex has been removed but, unlike the G8 group, the adatom is not linked to the facet opposite to the removed vertex but on an adjacent one. All the groups that are connected at Lid3 exhibit strong structural similarities, such that both the energy barriers and the entropic barriers are small enough to be crossed at this lid. At Lid4, there are only two changes. The set containing groups G10 and G13 is now linked to the set containing G1. This is the first connection between isomers based on a pyramid exhibiting either a missing vertex or a hole on one of its facets. The second change occurring at Lid4 is that the set containing G5+G18+G15 now also includes groups G3 and G19. At Lid5, there are paths on the potential energy surface that connect all the 19 groups.

Proximity and probability flows

In this section, we attempt to provide a picture of the basins' proximity on the PES as well as an analysis of the dominant probability flows, on the basis of the analysis of the threshold simulation performed at the highest lid, i.e. at 0.05 Hartree above the pyramid global minimum. This lid has been chosen as it is the first one to connect all the identified basins. In the supplementary materials, two figures S1 and S2 show all the probability flows p i→j between the 40 key isomers. These pictures show that some routes are favored with respect to others, motivating an extraction of dominant fluxes, which are depicted on figure 4. The top panel allows to visualize the main fluxes between isomer basins belonging to a given group Gx (called intragroup fluxes) whereas the bottom panel shows the main fluxes between groups (called intergroup fluxes).

In figure 4-top, an arrow represents an intragroup flux from a key isomers i to a key isomer j if p i→j is Fig. 4 Fluxes at Lid5. Top : Fluxes between key isomers within the 19 groups. The identifiers of the isomers are in green except if there is no significant flux within a given group (isomers in black), or if they correspond to an attractive basin (isomers in red). Bottom : Fluxes between the different groups. The colours of the boxes in the bottom figure identify the members of the 7 super-groups at Lid3. larger than 5 %. If a significant flux is present in both directions between two key isomers (p i→j and p j→i both larger than 5 %), then only the dominant flux is represented, except for the cases where the largest one is less than twice the smallest one. In the latter case, a double arrow is plotted. When two or more key isomers belong to the same group, the isomer identified as an attractor is depicted in red whereas a green color is used for the others. Starting with G1, an equilibrium is observed between the various pyramidal forms, particularly in the case of isomers 1 and 2, selected as starting points. In the groups G7, G8, G10 and G13, each one containing 2 key isomers, the lowest energy isomer (the one with the smallest index number) always appears as the at-tractive region of the group. A more complex picture is found for groups G16 and G9, which contain several key isomers. In group G16, the two lowest energy key isomers, namely 75 and 76, appear to correspond to non-attractive basins. This is also the case for isomer 86. Indeed, one-way-fluxes are observed from these isomers towards the three other ones (88, 90 and 78). Among them, the basin of the key isomer 78 appears to be the most attractive one. In group G9, the two lowest energy key isomers (18 and 19) do not correspond to attractive basins either. In this group, the attractive region corresponds to a pair of basins, namely those of isomers 20 and 30. These isomers seem to benefit from their intermediate position between two different parts of the PES, namely the one corresponding to isomer 29 and the one corresponding to isomers 18, 19, 25 and 26. As remarked above, in groups G9 and G16, the most attractive key isomer does not correspond to the one with the lowest energy. Actually, at a given lid energy, the relative fluxes between basins depends on their relative accessible phase space volume and this volume may or may not correlate with the depth of the minimum. Finally, groups G6 and G18 present a different picture as no intragroup flux could be identified. This is simply because each key isomer of these groups undergoes a very efficient transformation toward a more symmetric shape, joining, respectively, groups G1 (for G6 isomers) and G5 (for G18 isomers) before visiting other isomers of their own group. Obviously, the number of fluxes depicted in this figure depends on the p i→j limit value chosen for extracting the dominant fluxes. The choice of a limit value of 5 % was motivated by the intention to highlight the most likely paths only. Minority flows not taken into account in this analysis, i.e. with p i→j < 5%, can be observed in figure S2 of the supplementary information. From this figure, we can see for instance that with a p i→j limit value of 1%, all the isomers of G16 are connected.

We now address the intergroup fluxes. We first define for each key isomer i its outside group flux toward the group GJ as : p i→GJ = j∈GJ p i→j . We observed that the outside group fluxes are similar for all key isomers of a given group GI, allowing to define intergroup group fluxes; i.e. ∀i, i ∈ GI, p i→GJ p i →GJ P GI→GJ . 1 For each group GI, the main outside group flux (the largest value for P GI→GJ ∀GJ) is represented by an arrow in figure 4-bottom. When two groups are connected in both directions, the relative length of the two arrows is proportional to the relative intensity of these fluxes. The groups connected by arrows on fig-ure 4-bottom define a super-group. The first supergroup contains the pyramid group G1, which appears to be very attractive, as no simulation starting from this group visited another one, plus 6 other groups G2, G4, G6, G7, G9 and G16, all of them attracted by G1. In the other super-groups, probability flows occurring in two directions could be identified for four pairs of groups, namely G8 and G12; G11 and G14; G5 and G15; G10 and G13. In all cases, these fluxes correspond to small displacements of an adatom moving from the top of a triangle toward an edge. Although the present discussion is done for the highest lid (0.05 Ha) it is interesting to compare the connections made on the basis of these probability flows with those identified from the disconnectivity graph (figure 3). In figure 4-bottom, the colors represent the groups that are connected at Lid3. It appears that the flux based picture obtained here at Lid5 almost perfectly matches the connectivity map at Lid3. Indeed, the groups which are connected at Lid3 belong to the same super-group at Lid5, with the single exception of groups G19 and G3, which are not connected at Lid3. One should mention, however, that these two groups are connected at Lid4, together with groups G5, G15 and G18. This comparison of the disconnectivity graph and the main intergroup fluxes at Lid5 provides a consistent representation of the basins' proximity.

The G1 basin is the most attractive one and therefore the most likely to be observed; this nicely concurs with already reported results, such as the agreement between the experimental TIED spectrum and the slightly distorted Td isomer theoretical spectrum for Au - 20 [65,66]. Those authors concluded that the other investigated motifs such as icosahedron and decahedron can be clearly excluded as major contributors. This result was interpreted in terms of the energetic stability of the pyramid isomer with respect to the few other guessed structures. This is in line with our current work involving an unbiased exploration of the low-energy region of the landscape encompassing all relevant isomers and a study of the probablity flows taking energetic and entropic barriers into account. Note that the attractivity of the pyramid basin has also been reported from DFT-basin hopping explorations in the case of neutral Au 20 [107].

Dynamical evolution

The analysis of the probability flows allows for a detailed understanding of the structural deformations that occur when connecting different groups. When the transformation is not obvious, an additional analysis of the stopping points visited during the trajectory connecting two groups provides a complementary insight.

In our analysis, the intuitive migration of an adatom over the cluster surface never appeared to be an efficient way to connect two isomers. We have identified three main characteristic moves which are described in the paragraph below.

The first type of transformation is a global deformation of the cluster involving all atoms. In this category, one can find transitions between the pyramid G1 and the groups corresponding to a deformed pyramid, namely G2, G6, G9, G16, occurring at low energy (Lid2). The global deformation is also a way to connect two isomers through a third one that exhibits a mixture of their characteristic features. This is, for instance, the case in the transition from key isomer G3-6 (adatom close to the surface-hole) toward key isomer G5-9 (adatom far from the surface hole) which are connected at Lid5 through the key isomer G19-152. This isomer presents a surface hole and two atoms deviating from their position in the corresponding pyramid (one close and one far from the hole). A collective motion allows the one close to (respectively far from) the hole to recover its place as a vertex, the other one becoming the adatom, leading to key isomer G5-9 (respectively G3-6). The second transformation type is the displacement of an adatom close to a vertex from the top of a triangle toward the top of an edge. Such a transformation connects groups G8 and G12; G11 and G14; G5 and G15; G10 and G13 at Lid3 and above. The third type of transformation involves the migration of an atom to fill a hole in a facet center. Two illustrations of such trajectories are shown in figure 5, connecting the group G13 to groups G5 and G1, respectively. In the trajectory connecting the key isomers G13-39 and G5-9, the adatom (green) is almost not perturbed and the transformation proceeds via the migration of a facet atom (pink) through the center of the pyramid toward the hole, creating a new hole in its original position. In the second trajectory, G13-39 → G1-1, the recombination proceeds in a concerted mechanisms, an atom (pink) from an edge located between the hole and the adatom (green) moves toward the hole while its original place is taken by the adatom.

On the basis of this analysis, it is interesting to point out that the structural proximity of some isomers may lead to the design of intuitive paths that are actually not the most likely ones. As an example, it is intuitive to think that the key isomer G3-6 is connected to the pyramid group G1 through a simple motion of the adatom toward the hole. However, in our simulations G3 and G1 have only been connected at Lid5 through a more complex path involving two global cluster deformations (from G3-6 to G19-152 first and from G19-152 to G5-9) and one hole migration (G5-9 to G13-39, top line of figure 5) followed by the hole filling via the concerted mechanism from G13-39 to G1-1 (bottom of figure 5). In the same way, the key isomer G11-23 is not connected to the pyramid by a migration of the adatom on the surface to reach the depleted vertex. This isomer is actually connected to G1 via the migration of the adatom on top of a triangle toward an edge bridging position (G11-23 to G12-33) followed by global deformations (G12-33→G16-75→G1-1).

A similarly counter-intuitive pathway has been reported by Schebarchov et al. [108] for a larger neutral gold cluster, namely Au 55 . They observed that the intuitive rearrangement via adatom hops is not the fastest route to connect two close-packed isomers; instead, a concerted mechanism is more efficient. Interestingly, our conclusion regarding the paths where an adatom is filling a hole on a planar facet of an Au - 20 cluster is quite analogous to their observation of a concerted move sequence between two fcc-minima in Au 55 . We further note that rearrangement paths involving collective moves also appear to be dominant paths in small nanoalloys [131-133].

Conclusions

The threshold algorithm is a versatile tool to explore complex potential energy surfaces and, in particular, their barrier structure. It provides an overview of the groups of neighboring minima existing on the energy landscape and yields upper limits of the lowest energy barriers between them. In addition, it allows the identification of transition pathways connecting minima basins and individual minima and the measurement of the probability flows between them, thus yielding information about both energetic and entropic barriers on the landscape. Since unbiased explorations of energy landscapes require huge numbers of energy calculations, and such calculations are very expensive computationally for chemical systems on the ab initio level, we have incorporated the threshold algorithm in the DFTB deMonNano code [START_REF] Heine | deMon-Nano[END_REF]. Indeed, the computational efficiency of DFTB with respect to DFT makes it a tool of choice to investigate the energy landscape of intermediate and large systems, for which a quantum description is mandatory. This new DFTB/threshold scheme has been applied to the study of an anionic metal cluster : Au - 20 . This system exhibits a complex potential energy surface containing many isomers and a wide range of energy barriers, and requires a treatment at the quantum level to ensure that the landscape exhibits all relevant isomers in the correct energetic order and that the energetic and entropic barriers separating them are reliable.

G13-39

--------------------------------------------------------------------→ G5-9

G13-39 --------------------------------------------------------------------→ G1-1 The exploration allowed to identify 736 local minima on the PES. Among them, 40 key isomers have been identified using energetic and occurrence probability criteria. On the basis of geometrical considerations, these 40 key isomers could be distributed in 19 groups. Each group can be seen as corresponding to structures with a pyramidal shape with three specific variations : i/ distorted pyramids, ii/ pyramids in which the atom of one of the facets has been removed, leaving a hole, and placed either on the same facet, at different positions on another facet, or on an edge, and iii/ pyramids on which an atom located at a vertex has been removed and placed on an edge or on a facet. Upper limits of the energy barriers separating the different groups on the PES were evaluated, and at the highest investigated energy threshold (0.05 Ha), all groups were found to be connected. Furthermore, the probability flows between basins of the PES were analysed at this lid value, both inside each group and between different groups. This allowed us to define attractive isomers within groups and attractive groups. Interestingly, in a given group, the key isomer with the lowest energy was not always found to be the most attractive one. The analysis of the fluxes provided a representation of the Au - 20 basins' proximity in good agreement with the disconnectivity tree. Finally, detailed information about transition pathways between the various isomers has been obtained from the analysis of the threshold runs, leading to the identification of counter-intuitive transformation mechanisms. In particular, it appeared that the migration of an adatom over the Au - 20 cluster surface is not an efficient way to connect two isomers and that more complex concerted mechanisms are involved.

In summary, the suitability of the DFTB/threshold scheme developed in the present work has been clearly demonstrated in the context of the complex Au - 20 PES analysis. We believe that this work should pave the way toward applications to other systems, ranging from molecules to nanoparticles, both in vacuum and on surfaces.

Acknowledgements

This work was granted access to the HPC resources of the CALMIP supercomputing center (Grant p18009).

Supplemental Material

Cartesian coordinates of the lowest energy isomers of the 19 groups. Cartesian coordinates corresponding to the illustration of transition pathways depicted in figure 5 (from group G13 to group G5 and from group G13 to group G1). Probability flows between the 40 key isomers at Lid5.

Fig. 1

 1 Fig.1Structural excitation energies of isomers (eV). Black: the full set of 736 optimized isomers. Blue: the 40 key isomers (used as starting points for structural explorations, see text). Red: lowest energy isomers of the 19 identified structural groups and labels identifying the groups.

Fig. 2

 2 Fig. 2 Lowest energy isomers of the 19 groups.

Fig. 3

 3 Fig. 3 Disconnectivity graph showing the relative total energies (in eV) of the lowest energy isomers of the 19 groups with respect to the energy of the pyramid. The blue dashed lines indicate the energy lid positions.

Fig. 5

 5 Fig.5Illustration of transition pathways. Top: trajectory connecting the key isomers G13-39 and G5-9; the adatom (green) is almost not perturbed and the transformation proceeds via the migration of a facet atom (pink) through the center of the pyramid toward the hole, creating a new hole in its original position. Bottom: trajectory connecting the key isomers G13-39 and G1-1; the recombination proceeds in a concerted mechanisms, an atom (pink) from an edge located between the hole and the adatom (green) moves toward the hole while its original place is taken by the adatom. The cartesian coordinates corresponding to these pathways are given in Supplementary Material.

Fig. 6

 6 Fig. 6 TOC

Note that this also validates the use of the groupings as physically meaningful entities, possibly corresponding to large locally ergodic regions.