Manon Dechêne-Tempier

Eric Jouy

Marie-Hélène Bayon-Auboyer

Stéphanie Bougeard

Claire Chauvin

Virginie Libante

Sophie Payot

Corinne Marois-Créhan
email: corinne.marois@anses.fr

Antimicrobial resistance profiles of Streptococcus suis isolated from pigs, wild boars, and humans in France between 1994 and 2020

Keywords: Streptococcus suis, pathogen, antimicrobial resistance, CLSI, disc diffusion method

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

Introduction

Streptococcus suis is a zoonotic pathogen causing pig infections and substantial economic losses. Even though serotype 2 is preponderant, other serotypes can be responsible for infections worldwide [START_REF] Segura | Streptococcus suis Research: Progress and Challenges[END_REF]. In Europe, serotypes 9, 2 and 7 are dominant among clinical pig isolates (61%, 18% and 7% of the isolates, respectively) whereas serotypes 1/2 and 3 are also frequently found in the rest of the world [START_REF] Goyette-Desjardins | Streptococcus suis, an important pig pathogen and emerging zoonotic agent-an update on the worldwide distribution based on serotyping and sequence typing[END_REF][START_REF] Lacouture | Distribution and characterization of Streptococcus suis serotypes isolated from January 2015 to June 2020 from diseased pigs in Québec, Canada[END_REF]. Together with serotypes, Weinert et al. proposed to group S. suis strains into three groups or pathotypes according to their isolation sites: [START_REF] Segura | Streptococcus suis Research: Progress and Challenges[END_REF] "non-clinical", [START_REF] Goyette-Desjardins | Streptococcus suis, an important pig pathogen and emerging zoonotic agent-an update on the worldwide distribution based on serotyping and sequence typing[END_REF] "respiratory" or [START_REF] Lacouture | Distribution and characterization of Streptococcus suis serotypes isolated from January 2015 to June 2020 from diseased pigs in Québec, Canada[END_REF] "systemic" [START_REF] Weinert | BRaDP1T Consortium. Genomic signatures of human and animal disease in the zoonotic pathogen Streptococcus suis[END_REF]. These groups correspond to the [START_REF] Segura | Streptococcus suis Research: Progress and Challenges[END_REF] commensal, [START_REF] Goyette-Desjardins | Streptococcus suis, an important pig pathogen and emerging zoonotic agent-an update on the worldwide distribution based on serotyping and sequence typing[END_REF] possibly opportunistic, and [START_REF] Lacouture | Distribution and characterization of Streptococcus suis serotypes isolated from January 2015 to June 2020 from diseased pigs in Québec, Canada[END_REF] pathogenic groups defined by Estrada et al. [START_REF] Estrada | Serotype and genotype (multilocus sequence type) of Streptococcus suis isolates from the United States serve as predictors of pathotype[END_REF].

These authors also suggested using the serotype to predict the pathotype, as they demonstrated a link between serotypes and pathotypes [START_REF] Estrada | Serotype and genotype (multilocus sequence type) of Streptococcus suis isolates from the United States serve as predictors of pathotype[END_REF]. Human cases of S. suis were mainly described in Asia, with three large outbreaks in China reported in 1998, 2005 and 2016 [START_REF] Dong | The global emergence of a novel Streptococcus suis clade associated with human infections[END_REF]. Clinical manifestations of S. suis infection include meningitis, septicaemia, endocarditis and arthritis [START_REF] Salaneuve | Bilateral total deafness after preparation of wild boar meat[END_REF]. In France, human infections are scarce, the eighth French case since 1995 having been reported in 2016 [START_REF] Malézieux-Picard | Streptococcus suis Meningitis in a French Cooker: Case Report and Review[END_REF] and the latest case corresponds to a woman hospitalised for meningitis after preparing wild boar meat, with S. suis identified as the causative agent of the disease [START_REF] Salaneuve | Bilateral total deafness after preparation of wild boar meat[END_REF].

Several families of antimicrobials are commonly used in veterinary medicine to treat bacterial infections. These include tetracyclines, beta-lactams, polymyxins, macrolides-lincosamides, aminoglycosides, sulphonamides or trimethoprim-sulphonamides (TMPSs) [START_REF]Suivi des ventes de médicaments vétérinaires contenant des antibiotiques en France en[END_REF]. The antibiotic families mostly prescribed for gastrointestinal pig infections worldwide are tetracyclines, lincosamides, pleuromutilins and macrolides [START_REF] Jensen | A cross-sectional study of oral antibacterial treatment patterns in relation to specific diarrhoeal pathogens in weaner pigs[END_REF][START_REF] Hémonic | Reliable estimation of antimicrobial use and its evolution between 2010 and 2013 in French swine farms[END_REF][START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF][START_REF] Poissonnet | Panel INAPORC, suivi des usages d'antibiotiques en élevage de porcs en France entre 2010, 2016 et[END_REF]. Chlortetracycline, tetracycline and amoxicillin are used for treating respiratory and infectious diseases [START_REF] Apley | Use Estimates of In-Feed Antimicrobials in Swine Production in the United States[END_REF][START_REF] Van Rennings | Cross-sectional study on antibiotic usage in pigs in Germany[END_REF]. In France, tetracycline, beta-lactams (penicillins), macrolides and TMPSs are generally used for respiratory infections, polypeptides and tetracycline for sepsis and gastrointestinal infections [START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF]. beta-lactams (penicillins) are indicated for treating S. suis meningitis, septicaemia and/or arthritis [START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF]. In France, the regulation of antibiotics in veterinary medicine must meet French and European standards. The use of these molecules is subject to marketing authorisations and be indicated in the "Summary of product characteristics" (SPC) sheet. Checks are made on their distribution, prescription and use in accordance with European laws. In 2010, the European Union initiated a common European programme called "One Health" [START_REF]One Health[END_REF]. This programme is based on the premise that there is a direct link between human health, animal health and more generally environmental health. In 2012, France implemented its first "EcoAntibio" plan in order to reduce the use of antibiotics nationwide by more than 25% in 5 years. This plan was a success, as the use of antibiotics dropped by 37% [START_REF]Suivi des ventes de médicaments vétérinaires contenant des antibiotiques en France en[END_REF]. Resapath (a French surveillance network for antimicrobial resistance in bacteria from diseased animals) is part of the antimicrobial resistance surveillance system for animals set up in France. The Resapath network collects and analyses data from routine antimicrobial susceptibility tests (disc diffusion method) performed by diagnostic laboratories in the network, and publishes an annual report. For S. suis, this report includes the proportions of susceptible isolates for 12 antibiotics (amoxicillin, oxacillin, erythromycin, tylosin, spiramycin, lincomycin, streptomycin, kanamycin, gentamicin, tetracycline, doxycycline and trimethoprim-sulphonamides) [START_REF] Anses | Resapath -French surveillance network for antimicrobial resistance in bacteria from diseased animals[END_REF]. Except from Resapath, few data on the resistance of S. suis in France are available in the literature [START_REF] Hendriksen | Occurrence of antimicrobial resistance among bacterial pathogens and indicator bacteria in pigs in different European countries from year 2002 -2004: The ARBAO-II study[END_REF][START_REF] Morvan | Antimicrobial susceptibility of Streptococcus suis isolated from swine in France and from humans in different countries between 1996 and 2000[END_REF]. Therefore, the aim of this study was to investigate resistance of a collection of S. suis strains isolated in France to a larger number of antimicrobials. This collection of strains was fully characterised regarding serotype, and included strains isolated from humans and wild boars. The statistical associations between resistance/susceptibility and the isolation period, the strain's geographical origin, serotype, host and pathotype were analysed.

Materials and Methods

Bacterial strains

Two hundred isolates of S. suis were selected from the ANSES strain collection (n=1,619), resulting from different research programs, in order to get a set of strains representative of the diversity of serotypes, geographical origins and hosts available. All strains isolated from human cases or wild boar were selected. This set included 21 strains of serotype 1, 20 of serotype 1/2, 32 of serotype 2, 30 of serotype 3, 30 of serotype 7, 33 of serotype 9, and 34 strains of other serotypes (6 strains of serotype 4 and 1 or 2 strains of each of the following serotypes : 5, 8, 10, 11, 12, 14, 15, 16, 18, 21, 24, 27, 28, 29 and 31) (Table S1). In France, more than 50% of national swine production is based in Brittany, so we chose to include 130 strains collected in Brittany and 70 from other regions of France. Most of the strains were isolated from pigs (n=178); the remaining 22 were isolated from humans (n=13) or wild boars (n=9). Strains were allocated to two groups according to the isolation period (88 strains for the "before 2010" group, and 112 for "after 2015") to examine a potential impact of the French EcoAntibio plan. Finally, strains were classified into three pathotypes. The "systemic" group contained 127 strains isolated from samples of the nervous system, blood or joint when the causes of death were attributed to an infection by this pathogen. The "respiratory" group hosted 31 strains isolated from pulmonary samples obtained either from sick or clinically healthy animals on farms that had had outbreaks of S. suis infections. The strains in the "non-clinical" group (n=36) were from the upper respiratory tract with no sign of S. suis infection in animals and 6 strains were not classified due to a lack of information. More details can be found in the supplementary data (Table S1). All the strains used were confirmed by serotyping using the PCR method described by Okura et al. [START_REF] Okura | Development of a two-step multiplex PCR assay for typing of capsular polysaccharide synthesis gene clusters of Streptococcus suis[END_REF].

Culture conditions and antimicrobial susceptibility testing

All the strains were stored at -80°C in buffered peptone water solution with glycerol (20%).

Each strain was sub-cultured on Columbia Agar with 5% Sheep Blood (BIO-RAD®, Marne la Coquette, France) and incubated overnight at 37°C under 5% CO2. Antimicrobial susceptibility was tested using the disc (agar) diffusion method, according to Clinical Laboratory Standards Institute (CLSI) standards (VET01-A and VET01-S) [START_REF] Clsi | Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria from animals[END_REF][START_REF] Clsi | Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria from animals[END_REF]. Briefly, an inoculum of 1.10 8 CFU per mL was prepared for each strain and used to inoculate a Mueller-Hinton plate containing 5% of sheep blood (120-mm square plates, BIO-RAD®) before the application of antimicrobial discs (BIO-RAD, Marne-La-Coquette, France or Mast Diagnostics, Amiens, France). The plates were incubated 22 hours ± 1 hour at 35°C and, after bacterial growth, inhibition zone diameters were measured with a sliding calliper. The reference strain S.

pneumoniae ATCC 49619 was used as a quality control according to CLSI recommendations.

As S. suis is a zoonotic bacterium, the antimicrobials studied belong to either the veterinary or human medicine list or to both. For strains found resistant to penicillins and fluoroquinolones by disc diffusion method, the minimal inhibitory concentration was determined using MICRONAUT-S microplates (from MERLIN, Bruker). These microplates were used according to the manufacturer's instructions.

Strain categorisation

Antimicrobial susceptibility test results were used to differentiate between strains without or with acquired resistance mechanisms (wild-type (WT) or non-wild-type (NWT) respectively) using cut-off values (COWT). The normalised resistance interpretation (NRI) method was applied for each antibiotic to determine these COWT values. [START_REF] Kronvall | Normalized resistance interpretation, the NRI method: Review of NRI disc test applications and guide to calculations[END_REF][START_REF] Baron | Aeromonas Diversity and Antimicrobial Susceptibility in Freshwater-An Attempt to Set Generic Epidemiological Cut-Off Values[END_REF]. The NRI method applied to the disc diffusion antimicrobial susceptibility testing was precisely described by Kronvall and Smith [START_REF] Kronvall | Normalized resistance interpretation, the NRI method: Review of NRI disc test applications and guide to calculations[END_REF] and the related Excel program is freely accessible to the following website link: http://www.bioscand.se/nri/. The clinical interpretative criteria specified in CLSI [START_REF] Clsi | Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria from animals[END_REF] were also used when available. When the COWT calculation was not possible, the strain was categorised using the threshold diameters described in the literature and observations of the measured diffusion diameters (25)[START_REF] Hernandez-Garcia | Patterns of antimicrobial resistance in Streptococcus suis isolates from pigs with or without streptococcal disease in England between 2009 and 2014[END_REF][START_REF] Hayer | Prevalence and time trend analysis of antimicrobial resistance in respiratory bacterial pathogens collected from diseased pigs in USA between 2006-2016[END_REF]. In this study the WT term will be express as susceptible to the antibiotic tested and NWT will be express as resistant to the antibiotic tested.

Statistical analyses

The strains were classified according to different resistance profiles (Table S1) in proportion to their resistance/susceptibility to the antibiotics tested. In total, 24 resistance profiles were identified following the analyses carried out. The first (univariate) step entailed using a Chisquared test and Fisher correction (required for limited expected counts) to explore for each antibiotic possible links with other antimicrobial resistance rates together with links between each antimicrobial resistance profile and the isolation period, serotype, geographical origin, host and/or pathotype. The second (multivariate) step considered all the antimicrobial resistances. First, a multiple correspondence analysis (MCA) was performed to illustrate whether the antimicrobial resistance rates for the different antibiotics or the antimicrobial resistance profiles depend on the isolation period, serotype, geographical origin, host and/or pathotype (the latter variables being considered as supplementary in the analysis). Then, a multiple factor analysis (MFA) was used to determine whether there is a correlation between the antimicrobial resistance observed for the antibiotics of the same family and antibiotics of different families. For this purpose, each family was considered as a block of variables. In order to ensure robustness of the various tests and analyses, statistical analyses were performed only on groups with at least five representative strains. All the analyses were performed using the R software with the FactoMineR package [START_REF] Lê | FactoMineR: An R Package for Multivariate Analysis[END_REF]. Only results with a p-value equal to or lower than 0.05 were considered significant and subsequently interpreted.

Results

Determination of cut-off values using the NRI method

The NRI method applied to the distributions of inhibition zone diameters can be used to define two groups corresponding to the two observed populations divided by the COWT (Table 1).

Only one population was observed for gentamicin, chloramphenicol, florfenicol, linezolid, quinupristin/dalfopristin and vancomycin. Two were observed for ampicillin, penicillin, cefotaxime, ceftiofur, imipenem, clindamycin, lincomycin, erythromycin, tilmicosin, tylosin, enrofloxacin, levofloxacin, norfloxacin and trimethoprim-sulphamethoxazole. Finally, a complex pattern was observed for tiamulin and tetracycline. In the absence of CLSI clinical interpretative criteria, the COWT value was therefore determined manually for tiamulin and the CLSI's interpretive criteria for Streptococcus spp. were used for tetracycline.

Antibiotic susceptibility of the strains

No resistance was observed for the following antibiotics: Gentamicin (aminoglycosides) (to high concentration levels), linezolid (oxazolidinones), quinupristin/dalfopristin (streptogramins) and vancomycin (glycopeptides) (Table 1). For phenicols (chloramphenicol and florfenicol), the NRI COWT and the breakpoints proposed by the CLSI differed by only two and one millimetre respectively, which could lead to different interpretations for 18 strains.

It was decided to use the cut-off calculated by the NRI method and to classify all the strains as susceptible to this family of antibiotics. Indeed, no strain differed from the wild-type population for these two antimicrobials.

The resistance rates observed are reported in Figure 1. Less than 1% of the strains tested were resistant to fluoroquinolones (this single strain was resistant to enrofloxacin, levofloxacin and norfloxacin). Five percent of the strains tested showed beta-lactam resistance, with ten strains resistant to penicillin G. Of these, three were also resistant to ampicillin. These results were confirmed by MIC determination of penicillin G: 2 µg/mL for three strains, 1 µg/mL for four strains, 0.5 µg/mL for one strain and 0.25 µg/mL for two strains. For ampicillin, MIC was 1 µg/mL for three strains. The breakpoints used were >0.12 µg/mL for penicillin G and >0.25 µg/mL for ampicillin (CLSI M100) [START_REF] Lê | FactoMineR: An R Package for Multivariate Analysis[END_REF]. No strain was resistant to cefotaxime, ceftiofur or imipenem. For pleuromutilin (tiamulin) and diaminopyrimidine-sulphonamides (TMPS), the proportions of resistant strains were 8% (n=16) and 16% (n=32) respectively. One of the highest resistance percentages observed was for macrolides-lincosamides, with more than 71% of the strains tested having resistance profiles (to erythromycin, 69% (n=137), tilmicosin, 69% (n=137), tylosin 69% (n=138), to clindamycin 71% (n=142) and lincomycin 71% (n=142)).

Finally, 81% of the tested strains were resistant to tetracycline (n=162). In total, 86% of the strains tested were resistant to at least one antibiotic (n=171). Among these isolates, 138 can be classified as multi-resistant as they are resistant to three families of antibiotics. Thirty-five, eight and three strains were resistant to respectively four, five or six families of antibiotics. The resistance patterns are included in the supplementary data (Table S2). The most common multi-resistance patterns observed in this study are for macrolides (erythromycin, tilmicosin, tylosin) associated with lincosamides (clindamycin, lincomycin) and tetracycline (97 strains, profile P11), followed by macrolides-lincosamides, tetracycline and trimethoprim-sulphamethoxazole (20 strains, profile P15).

Prevalence of antimicrobial resistance according to the isolation period, serotype, geographical origin, host and pathotype

A significant decrease in resistance to TMPS occurred between the two periods, with a proportion of resistant strains dropping from 23.5% (20/85) before 2010 to 10.4% (12/115) after 2015 (p < 0.035).

Serotype 2 was over-represented among lincomycin-susceptible strains, with 20 strains out of 61, i.e. 33% (p = 0.001). Interestingly, penicillin resistance was associated (p < 0.001) with less common serotypes (two strains of serotypes 11 and 12, and one strain of serotypes 1, 5, 9, 15, 27 and 29). A similar result was observed for tiamulin-resistant strains, there being an overrepresentation of the serotypes classified under "others ", with seven strains out of sixteen from serotypes 1 or 9 (three and four strains respectively) compared with nine strains from serotypes 5, 12, 15, 16, 27, 29 and 31 (1, 2, 1, 1, 1, 1 and 2 strains respectively) (p < 0.001). Strains with these serotypes are less frequent and thus less studied than the others. Finally, among the thirtytwo TMPS-resistant strains, there was an over-representation (p <= 0.01) of serotypes "1/2" (nine strains), "others" (seven strains) and serotype 3 (six strains).

The resistance profiles of the strains can also be correlated with their geographical origin. An over-representation of resistance to the macrolide and lincosamide families and penicillin was observed in strains collected in Brittany (erythromycin p = 0.017, tilmicosin p = 0.017, tylosin p = 0.012, clindamycin p = 0.019, lincomycin p = 0.019, and penicillin p = 0.016).

Furthermore, strains isolated from humans or wild boars appear to have fewer acquired resistance mechanisms to macrolides (erythromycin p < 0.001, tilmicosin p < 0.001, tylosin p < 0.001), lincosamides (clindamycin p = 0.002, lincomycin p = 0.001) and tetracycline (p= 0.003) than strains isolated from pigs. However, these results must be taken with caution since in the collection the number of strains isolated from humans or wild boar (n=22) is much lower than the number of strains isolated from pigs (n=178).

Finally, regarding the correlations between resistance profiles and pathotypes, penicillin and TMPS resistances are more frequently found in "non-clinical" or "respiratory" isolates (p < 0.001, p = 0.011 respectively) than in systemic isolates.

The multiple factor analysis (MFA), confirmed by Chi-squared test, revealed an association between antimicrobial resistances to tetracycline, macrolides (tylosin, erythromycin, tilmicosin) and lincosamides (lincomycin and clindamycin) (p < 0.001) and between resistances to penicillin and tiamulin (p < 0.001) (Figure 2 (A)). An association between TMPS resistance and lincosamides (lincomycin and clindamycin) resistance was also observed but to a lesser extent (p = 0.042).

additional variables (resistance profiles) (the correspondence table of the resistance

profiles is available as additional data, Table S2).

The multiple correspondence analysis (MCA) (Figure 2 (B)) and Chi-squared test revealed a statistically significant link between a systemic pathotype and an antimicrobial resistance to macrolides and/or lincosamides and/or tetracyclines. A significant link was also found between the serotype "others", the geographical origin "Brittany", the pathotypes "non-clinical" or "respiratory" and resistance to beta-lactams and pleuromutilin. The Chi-squared test also showed the influence of serotypes and pathotypes on the resistance profiles observed in this study (p < 0.001 and p < 0.001 respectively).

Discussion

The strains with an acquired resistance mechanism were differentiated from those without (nonwild type versus wild type) by calculating the COWT values of 22 antibiotics using the NRI method. When the COWT calculation was not possible, the strain was categorised using the threshold diameters described in the literature (25)[START_REF] Hernandez-Garcia | Patterns of antimicrobial resistance in Streptococcus suis isolates from pigs with or without streptococcal disease in England between 2009 and 2014[END_REF][START_REF] Hayer | Prevalence and time trend analysis of antimicrobial resistance in respiratory bacterial pathogens collected from diseased pigs in USA between 2006-2016[END_REF] and observations of the measured diffusion diameters. Five antibiotics are documented with MIC for S. suis in the CLSI's VET01S [START_REF] Clsi | Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria from animals[END_REF] (penicillin G, ceftiofur, enrofloxacin, florfenicol and tetracycline) but interpretation diameters are given for only two of them (ceftiofur and florfenicol). The COWT values obtained with the NRI method for ceftiofur and florfenicol in this work do not differ more than two millimetres from the interpretation diameters indicated in the CLSI's VET01S

for S. suis [START_REF] Clsi | Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria from animals[END_REF]. Likewise, the interpretation diameters indicated for Streptococcus spp only differ by two millimetres at most from the COWT values obtained with the NRI method for chloramphenicol and vancomycin.

No strain appeared resistant to linezolid (oxazolidinone), quinupristin-dalfopristin (streptogramins A+B), vancomycin (glycopeptides) and gentamicin (to high concentration level). Oxazolidinone (linezolid) appears to be very efficient against most Gram-positive bacteria, including pathogens of importance for human health (29). To our knowledge, S. suis resistance to linezolid and more broadly to the oxazolidinone family has only been reported in Asia in recent years [START_REF] Wang | First report of the multiresistance gene cfr in Streptococcus suis[END_REF][START_REF] Huang | Retrospective analysis of genome sequences revealed the wide dissemination of optrA in Gram-positive bacteria[END_REF][START_REF] Du | Characterization of a Linezolid-and Vancomycin-Resistant Streptococcus suis Isolate That Harbors optrA and vanG Operons[END_REF][START_REF] Huang | Identification and pathogenicity of an XDR Streptococcus suis isolate that harbours the phenicol-oxazolidinone resistance genes optrA and cfr, and the bacitracin resistance locus bcrABDR[END_REF][START_REF] Yang | Two novel lsa(E)-carrying mobile genetic elements in Streptococcus suis[END_REF]. Two genes conferring two types of resistance mechanisms are known in the literature, the cfr gene (coding an rRNA methyltransferase) and the optrA gene (coding an ABC transporter) [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. The absence of resistance to linezolid in our collection of strains confirms that this resistance is not present or very rare in S. suis in France.

Streptogramins are used against numerous highly-resistant pathogens and are therefore classified as antibiotics for last-resort human therapy [START_REF] Mast | Streptogramins -Two are better than one![END_REF][START_REF] Who | Advisory Group on Integrated Surveillance of Antimicrobial Resistance. Critically important antimicrobials for human medicine: ranking of antimicrobial agents for risk management of antimicrobial resistance due to non-human use[END_REF]. Streptogramin A resistance in S.

suis conferred by the cfr gene and lsa(E) gene (coding an ABC transporter) has only been described in a few genomics studies [START_REF] Shen | Presence and dissemination of the multiresistance gene cfr in Gram-positive and Gram-negative bacteria[END_REF][START_REF] Wang | First report of the multiresistance gene cfr in Streptococcus suis[END_REF][START_REF] Yang | Two novel lsa(E)-carrying mobile genetic elements in Streptococcus suis[END_REF][START_REF] Bojarska | Streptococcus suis in invasive human infections in Poland: clonality and determinants of virulence and antimicrobial resistance[END_REF][START_REF] Hadjirin | Large-scale genomic analysis of antimicrobial resistance in the zoonotic pathogen Streptococcus suis[END_REF]. These genes are combined with an erm(B) gene in order to provide resistance to the quinupristin-dalfopristin combination tested in our work. Vancomycin is among the last-resort antimicrobial agents for the treatment of multidrug-resistant Gram-positive bacterial infections [START_REF] Huang | Emergence of a vanG-carrying and multidrug resistant ICE in zoonotic pathogen Streptococccus suis[END_REF]. Resistance to vancomycin has been reported in China but not yet in Europe and more specifically in France, to our knowledge [START_REF] Du | Characterization of a Linezolid-and Vancomycin-Resistant Streptococcus suis Isolate That Harbors optrA and vanG Operons[END_REF][START_REF] Huang | Emergence of a vanG-carrying and multidrug resistant ICE in zoonotic pathogen Streptococccus suis[END_REF]. This can be explained by the difference in use specific to each country and the nature of this resistance, as resistance is due to the presence of the VanG-type resistance operon [START_REF] Huang | Emergence of a vanG-carrying and multidrug resistant ICE in zoonotic pathogen Streptococccus suis[END_REF]. S.

suis has a naturally low level of resistance to aminoglycosides. This family of antibiotics is Among the 200 strains tested, 5% were resistant to at least one antibiotic of the beta-lactam family. In France, the Resapath network registered a resistance rate to beta-lactams lower than 5% in 2019 [START_REF] Anses | Resapath -French surveillance network for antimicrobial resistance in bacteria from diseased animals[END_REF]. In Asia, the resistance rate to ampicillin (0.6-23% before 2010) is higher than both North America (2.3-3% before 2010 and 0.6% after 2010), and South America (0.5%) (25,[START_REF] Hayer | Prevalence and time trend analysis of antimicrobial resistance in respiratory bacterial pathogens collected from diseased pigs in USA between 2006-2016[END_REF][START_REF] Matajira | Streptococcus suis in Brazil: Genotypic, virulence, and resistance profiling of strains isolated from pigs between 2001 and 2016[END_REF]. Resistance to ampicillin was reported to be lower than resistance to penicillin or ceftiofur [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. This is the case in our study for penicillin, with three strains resistant to ampicillin and ten strains resistant to penicillin G. A decrease in penicillin G resistance has been observed

in North America (14-14.5% before 2010 dropping to 6.9% after 2010) whereas the resistance rate remains stable in Asia and Europe (respectively 0.9-27% and 13.5% in Asia and 0-13% and 2.6-5% in Europe before and after 2010) (25,[START_REF] Zhang | Capsular serotypes, antimicrobial susceptibility, and the presence of transferable oxazolidinone resistance genes in Streptococcus suis isolated from healthy pigs in China[END_REF]. In this study, no difference between the two time periods were observed, in accordance with the literature. Overall, the resistance rate measured in this study is similar to the rate reported in Europe (Denmark, England and Sweden) but lower than the rate measured in North America and Asia (25-27, 41, 43). Penicillinsand especially amoxicillinis the molecule used for first-line treatment of S. suis infections. Thus, investigations were pursued on the ten S. suis strains resistant to beta-lactams. Determination of the MIC indicated that ten strains were resistant to penicillin. All the strains resistant to penicillin were isolated from pigs in Brittany, and were categorised as "non-clinical" for five strains, "respiratory" for one strain and "systemic" for one strain, while the pathotype of three other strains was unknown. The resistant strains belong to various serotypes and were isolated at different periods of time: serotypes 1 (1 strain), 5 (1 strain ), 9 (1 strain), 11 (2 strains), 12 (2 strains), 27 (2 strains), and 29 (1 strain). In this study, none of the strains tested was resistant to cephalosporins. This is in accordance with the much lower level of resistance to cephalosporin described in Europe (0.7% before 2010 and 0% after 2010) than in Asia and North America (0.6-23% before 2010 and 0.9% after 2010 for Asia and 1-23.1% before 2010 and 9.3% after This agrees with the association between resistance to tetracycline and macrolides-lincosamides detected by MFA. This resistance pattern is the most frequently described in the literature and generally results from a co-localisation of a tetracycline resistance gene with an erm(B) gene on mobile genetic elements (25-27, 35, 41, 42, 44, 47). Macrolides and tetracyclines are among the most frequently used antibiotics in pig production worldwide [START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF]. The World Health Organization has also defined them, among others, as critically (macrolides) or highly (lincosamides and tetracyclines) important antimicrobials for human medicine [START_REF] Mast | Streptogramins -Two are better than one![END_REF]. In our study, antibiotics used exclusively in veterinary or human medicine as well as antibiotics used in both spheres were tested against strains isolated from swine, wild boars, and humans. There do not appear to be differences in the resistance profiles of these strains in terms of the type of medical field in which these antibiotics are used. The strain collection used for our study includes a small number of human (n = 13) and wild boar (n = 9) isolates and it would be beneficial to test more strains in order to confirm these results. However, this shows the presence of these resistance genes as well as their persistence given the lack of selection pressure for some molecules. Among all the strains tested (200), three showed resistance to six antimicrobial families: beta-lactams, macrolides, lincosamides, pleuromutilins, tetracyclines and trimethoprim-sulphamethoxazole. These strains belong to the least represented serotypes (5, 27 and 29) in our collection and were of non-determined pathotype "not determined", "nonclinical" and "respiratory" isolates respectively.

In order to observe a potential impact of the French EcoAntibio plan intended to reduce the prescription, sale and consumption of antibiotics, we analysed strains isolated before 2010 and strains isolated after 2015. A significant change (p = 0.035) in the TMPS resistance rate was observed (63% of resistant strains before 2010 and 38% after 2010) in our collection. Between 2011 and 2019, the exposure of pigs to this antimicrobial fell by 60.6% in France [START_REF] Anses | Resapath -French surveillance network for antimicrobial resistance in bacteria from diseased animals[END_REF], which could have a positive impact on the reduction of TMPS resistance in S. suis. In France, more than half of national pig production is concentrated in Brittany. Overall, strains from this region appear significantly more resistant than those from other French regions. In the literature, the impact of the close proximity of pigs on the spread of resistance has already been studied at the scale of a few herds [START_REF] Niemann | Antimicrobial susceptibility and genetic relatedness of respiratory tract pathogens in weaner pigs over a 12-month period[END_REF] or in a country, and the link between the intensity of animal production and the spread of resistance has been proven [START_REF] Hayer | Prevalence and time trend analysis of antimicrobial resistance in respiratory bacterial pathogens collected from diseased pigs in USA between 2006-2016[END_REF][START_REF] Hadjirin | Large-scale genomic analysis of antimicrobial resistance in the zoonotic pathogen Streptococcus suis[END_REF][START_REF] Holmer | Antibiotic resistance in porcine pathogenic bacteria and relation to antibiotic usage[END_REF].

Some resistances were associated with particular serotypes. This is the case for penicillin resistance found in infrequent serotypes. Further studies are needed to explain these associations. It has been suggested that the serotype could predict the pathotype of S. suis strains [START_REF] Estrada | Serotype and genotype (multilocus sequence type) of Streptococcus suis isolates from the United States serve as predictors of pathotype[END_REF]. The significant link observed in our study between "non-clinical" or "respiratory" and serotypes other than serotypes 1, 2, 7 and 9 (serotypes called "other") supports this hypothesis.

In addition, Hadjirin et al. pointed out a higher MIC in non-clinical isolates [START_REF] Hadjirin | Large-scale genomic analysis of antimicrobial resistance in the zoonotic pathogen Streptococcus suis[END_REF]. In our study, a statistically significant link was observed between the pathotypes "non-clinical" or "respiratory" and resistance to penicillin and pleuromutilins. This agrees with a previous report on resistance to beta-lactams mainly found in commensal strains [START_REF] Segura | Streptococcus suis Research: Progress and Challenges[END_REF]. It would therefore be beneficial to study these strains, which could serve as a reservoir of resistance genes. Weinert et al. suggested that the respiratory tract is more ecologically diverse than systemic locations (4). This environment could facilitate the appearance of resistance mutations and horizontal gene transfer of mobile genetic elements. Since most resistance genes are carried by mobile genetic elements in S. suis [START_REF] Libante | Chromosomal Conjugative and Mobilizable Elements in Streptococcus suis: Major Actors in the Spreading of Antimicrobial Resistance and Bacteriocin Synthesis Genes[END_REF], this would lead to an enrichment of "non-clinical" strains in resistance genes. To effectively combat antibiotic resistance, it appears vital to improve understanding of antimicrobial resistance in all serotypes, but especially those not frequently studied, but which can act as a reservoir of resistance genes for other bacteria.

Figure 1 :

 1 Figure 1: Resistance rates observed for 200 S. suis strains. The percentage of strains without or

Figure 2 :

 2 Figure 2: Comparative analysis of the resistance profiles of 200 strains of S. suis isolated in

169 170 Table 1 :

 1701 Normalised Resistance Interpretation cut-off value obtained with the disc diffusion 171 method for 200 S. suis strains.

	172
	Class	Antimicrobial agent	Disc load	Distribution	NRI cut-off	CLSI	Wild-type	Non-wild-type
			(µg)	pattern	value (mm)*	(mm)**	population	population
							(mm)	(mm)
	Aminoglycosides	Gentamicin	500	Unimodal	23		23-39	NA 2
	β-Lactams	Ampicillin	2	Multi-modal	23		24-38	13-22
		Penicillin G	1	Multi-modal	19		19-32	6-17
		Cefotaxime	30	Multi-modal	24		24-38	NA 2
		Ceftiofur	30	Multi-modal	24	≥21 (S) S.	24-36	NA 2
						suis
		Imipenem	10	Multi-modal	30		32-44	NA 2
	Phenicols	Chloramphenicol	30	Unimodal	19	≥21 (H)	19-30	NA 2
						Streptococcus
						spp.
		Florfenicol	30	Unimodal	21	≥22 (S) S.	21-34	NA 2
						suis
	Lincosamides	Clindamycin	2	Multi-modal	20	≥19 (H)	20-29	6-19
						Streptococci
		Lincomycin	15	Multi-modal	22		22-32	6-21
	Macrolides	Erythromycin	15	Multi-modal	22	≥21 (H)	32-24	6-17
						Streptococci
		Tilmicosin	15	Multi-modal	10		10-21	6
		Tylosin	30	Multi-modal	18		18-27	6-16
	Fluoroquinolones	Enrofloxacin	5	Multi-modal	18		20-34	14
		Levofloxacin	5	Multi-modal	18		18-32	14
		Norfloxacin	10	Multi-modal	13		16-29	6-10
	Pleuromutilins	Tiamulin	30	Multi-modal	NA 1		14-29	6-13
	Oxazolidinones	Linezolid	30	Unimodal	22		24-37	NA 2
	Streptogramins	Quinupristin/Dalfopris	15	Unimodal	15		15-27	NA 2
		tin
	Tetracycline	Tetracycline	30	Multi-modal	NA 1	≥23 (H)	23-33	6-22
						Streptococcus
						spp.
	Diaminopyrimidines-	Trimethoprim-	25	Multi-modal	12		12-31	6-11
	sulphonamides	Sulphamethoxazole
	Glycopeptides	Vancomycin	30	Unimodal	18	≥17 (H)	20-32	NA 2
						Streptococcus
						spp.

*NRI cut-off calculated for 22 antibiotics. **Interpretive criteria provided by the CLSI (22) for 173 Swine (S) or Human (H). NA 1 , no diameter cut-off available. NA 2 , no values for the non-wild-174 type clusters. The CLSI Breakpoint and NRI cut-off are both expressed in millimetres, as are 175 the values obtained for the wild-type and non-wild-type clusters. 176 177

Acknowledgments

The automatic and manual excel programs used for the cut-off values were made available through the courtesy of P. Smith, W. Finnegan, and G. Kronvall.

Funding

This research received no external funding, MDT was supported by ANSES and INRAE.

currently used in combination with beta-lactams in veterinary practice and is among the critically important antimicrobials [START_REF] Who | Advisory Group on Integrated Surveillance of Antimicrobial Resistance. Critically important antimicrobials for human medicine: ranking of antimicrobial agents for risk management of antimicrobial resistance due to non-human use[END_REF]. High-level resistance to aminoglycosides is due to several genes encoding three types of target modification enzymes leading to their inactivation, and are encoded by the aac, aph and ant genes [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. The Resapath network indicated the presence in France of a low rate (<2%) of high-level resistance in S. suis isolated from diseased pigs in 2019 (2% for streptomycin, 4% for kanamycin, 0% for gentamicin) [START_REF] Anses | Resapath -French surveillance network for antimicrobial resistance in bacteria from diseased animals[END_REF]. Our results are therefore in accordance with Resapath findings.

Using the NRI cut-off, none of the S. suis strains appeared resistant to the two phenicols tested (chloramphenicol and florfenicol). The resistance mechanisms to phenicols are mediated by the cfr and optrA genes discussed above, which confer resistance to linezolid. Another resistance mechanism is chloramphenicol acetyl-transferase mediated by the cat gene [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. In Europe, phenicol resistance in S. suis is less common than in Asia [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. Thus, the absence of resistance observed in this study is consistent with the observations reported in the literature [START_REF] Hendriksen | Occurrence of antimicrobial resistance among bacterial pathogens and indicator bacteria in pigs in different European countries from year 2002 -2004: The ARBAO-II study[END_REF][START_REF] Hernandez-Garcia | Patterns of antimicrobial resistance in Streptococcus suis isolates from pigs with or without streptococcal disease in England between 2009 and 2014[END_REF].

Only one strain resistant to fluoroquinolones was identified in our collection. The resistance was confirmed by MIC determination. This serotype-5 strain, isolated in 2009, has a multiresistance profile as it is also resistant to macrolides-lincosamides, tetracycline, pleuromutilin, diaminopyrimidine-sulphonamide and penicillins. In Asia, the reported resistance rate to enrofloxacin is higher (21-32.8% before 2010 and 28.8% after 2010) than in both Europe (2% before 2010 and 1-5.3% after 2010), and North America (1.4% between 2006 and 2016) (25,[START_REF] Hayer | Prevalence and time trend analysis of antimicrobial resistance in respiratory bacterial pathogens collected from diseased pigs in USA between 2006-2016[END_REF][START_REF] Holmer | Antibiotic resistance in porcine pathogenic bacteria and relation to antibiotic usage[END_REF][START_REF] Werinder | Streptococcus suis in Swedish grower pigs: Occurrence, serotypes, and antimicrobial susceptibility[END_REF][START_REF] Zhang | Capsular serotypes, antimicrobial susceptibility, and the presence of transferable oxazolidinone resistance genes in Streptococcus suis isolated from healthy pigs in China[END_REF]. The resistance rate measured in our work is consistent with the rate measured in Europe. Fluoroquinolone usage represents 2.4% of the total use of antibiotics in global pig production [START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF]. Two types of resistance mechanisms have been described in the literature: mutations in the targets of fluoroquinolones (DNA gyrase and topoisomerase IV) and efflux by an ABC transporter (sat(A) and sat(B) genes) [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. by Resapath but in the range described in Europe (up to 75% for erythromycin and 8% to 87.4% for clindamycin) (25). The erythromycin resistance rate increased in Asia after 2010 (96.8% in China) (43) but appears to have decreased in some European countries (48% in Denmark and 46% in England) [START_REF] Hernandez-Garcia | Patterns of antimicrobial resistance in Streptococcus suis isolates from pigs with or without streptococcal disease in England between 2009 and 2014[END_REF][START_REF] Holmer | Antibiotic resistance in porcine pathogenic bacteria and relation to antibiotic usage[END_REF]. Variations in the rate of resistance to macrolides-lincosamides are observed worldwide, possibly explained by the usage of macrolides in pig production [START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF]. In our study, differences in resistance were observed according to the geographical origin of the strains and the host, with a significant concentration of resistance in porcine isolates from Brittany.

A high proportion of resistance was also observed for tetracycline (81%) in accordance with the data from the Resapath network [START_REF] Anses | Resapath -French surveillance network for antimicrobial resistance in bacteria from diseased animals[END_REF], which reported a resistance rate of 79% to tetracycline for S. suis isolated from pigs in 2019. In North America and Asia, resistance rates measured for tetracycline (87-100%, 86.9-96% respectively) were higher for strains isolated before 2010. In Europe, the resistance rate before 2010 was relatively heterogeneous, ranging from 48% in the Netherlands to 95.4% in Spain (25). After 2010, tetracycline resistance rates in Asia (97.8% in China) and Europe (75% in Denmark and 91% in England) were still high [START_REF] Hernandez-Garcia | Patterns of antimicrobial resistance in Streptococcus suis isolates from pigs with or without streptococcal disease in England between 2009 and 2014[END_REF][START_REF] Holmer | Antibiotic resistance in porcine pathogenic bacteria and relation to antibiotic usage[END_REF][START_REF] Zhang | Capsular serotypes, antimicrobial susceptibility, and the presence of transferable oxazolidinone resistance genes in Streptococcus suis isolated from healthy pigs in China[END_REF]. In North America, resistance to oxytetracycline was also high (95.4%) [START_REF] Hayer | Prevalence and time trend analysis of antimicrobial resistance in respiratory bacterial pathogens collected from diseased pigs in USA between 2006-2016[END_REF]. These observations are explained by the worldwide use of tetracyclines in all pig production stages (1st class of antibiotics used) [START_REF] Lekagul | Patterns of antibiotic use in global pig production: A systematic review[END_REF]. In our study, no change was observed in the rate of tetracycline resistance between the two time periods studied. As for macrolides-lincosamides, resistance to tetracyclines was higher in pigs than in humans or wild boars. The mechanisms of tetracycline resistance have been well studied. They include efflux pumps and ribosome protection proteins [START_REF] Dechêne-Tempier | Update on the mechanisms of antibiotic resistance and the mobile resistome in the emerging zoonotic pathogen Streptococcus suis[END_REF]. The existence of numerous resistance genes may explain the diversity of the inhibition diameters observed.

In our study, 138 strains were classified as multi-resistant. Among them, the most common resistance pattern observed was the macrolides-lincosamides-tetracycline pattern (97 strains).

Supplementary Materials

All the data obtain with the Anses strains and use in this paper are presented in Tables S1 andS2.

Conflicts of Interest

The authors declare no conflict of interest.


K Sieja

Brink-Axel hypothesis in the pygmy-dipole resonance region

Keywords: XX, XX, XX No code given

The Brink-Axel hypothesis, which states that the photoabsorption cross section is independent of the excitation energy of a nuclear system, is an assumption used in nuclear structure studies and calculations of neutron-capture cross section for astrophysical applications. In the present work, using microscopic Configuration Interaction method, it is demonstrated that the dipole photoabsorption cross section at low energy is dependent on the excitation energy and deviations from the Brink-Axel hypothesis are particularily large for the ground state of an even-even system. It is also shown that the low-lying E1strength, known as pygmy dipole resonance, is redistributed with the excitation energy of the initial state and strongly dependent on its structure. The consequences of these findings on the calculated neutroncapture cross sections are discussed.

The γ strength functions (γ-SF) are fundamental properties of the atomic nucleus and basic inputs for the evaluation of neutron capture cross sections, which play a central role in astrophysical models of nucleosynthesis and stellar evolution [1,2]. They are also necessary to optimize the design of nuclear power reactors and to determine the ideal parameters for the burnup of nuclear waste [3]. All electromagnetic multipoles may contribute to the γ-SF but the electric dipole (E1) seems to dominate with some contribution of the magnetic dipole (M 1) transitions. Above the particle threshold, E1 γ-SF is governed by the isovector giant dipole resonance (GDR) but at lower excitation energies the situation is more complex: In nuclei with neutron excess one observes an enhancement of the low-energy strength, known as pygmy dipole resonance (PDR). The PDR provides constraints on such fundamental properties as the neutron-skin thickness of medium to heavy nuclei [4,5], the nuclear symmetry energy [6], and the properties of neutron stars [7]. As it is located near particle threshold, its impact on astrophysical reaction rates and the resulting abundances in the r process was underlined e.g., in [8][9][10]. In stellar environements one deals with finite temperatures, thus reactions on excited states become of interest and the validity of the Brink-Axel hypothesis (BAH) appears crucial [11,12]. Introduced in 1955, it states in its primary form that the energy-smoothed photoabsorption cross section is independent of the detailed structure of initial state, so that the γ-SF should depend on the γ energy only. Later on the hypothesis was generalized to affirm that the γ-SF should be the same in γ-absorption and emission experiments. Experimentally it is not trivial to test the hypothesis in an energy range wide enough for firm conclusions. Validity of the BAH in the quasi-continuum of nuclear states was established using the Oslo method, see e.g. [13] and references therein. The BAH in the PDR region was validated in [14], contrary to earlier claims of [15,16]. In two very recent experiments, deviations from the BAH were again noticed [17]. The most recent verification performed in 116,120,124 Sn [18] found only a small contribution of the PDR peaks to the decay γ-SF. An open question remained to which extent these findings could be generalized. Theoretical studies also put the assumptions of the BAH in question. In Ref. [19] evolution of sum rules of transition operators with initial energy was achieved within the Configuration Interaction approach (CI, known as well as interacting shell model or configuration interaction shell model), suggesting only weak violations of the BAH in the case of the E1 operator. Other theoretical studies do not support the BAH for E1 transitions: The thermally unblocked relativistic quasiparticle random-phase approximation (QRPA) of [20] pointed out different shapes of γ-SF with increasing temperature. In [21] the E1 deexcitation γ-SF was studied in the CI and its low-energy part shown to differ considerably from the GDR built on the ground state (g.s.) which resulted in addition of empirical non-zero limits to the QRPA γ-SF to describe the radiative decay in Ref. [22]. A conclusion invalidating the BAH was reached also in [23] where the temperature dependence of the γ-SF including M 1, E1 and E2 transitions was studied within the phonon damping model. This Letter focuses on the assumptions of the generalized BAH for the dipole γ-SF with an emphasis on the E1 strength in the PDR region. Two aspects are adressed: (i) the changes of the photoabsorption γ-SF depending on the initial state, (ii) the equivalence between photoabsorption ("upward") and deexcitation ("downward") strengths. To this end, CI calculations of the E1 + M 1 γ-SF in neutronrich nuclei are performed, taking as example neon isotopes (Z = 10): 26 Ne was reported to exhibit a pygmy resonance [24] which is reproduced by present CI calculations. Evolution of dipole strength with the neutron number and modifications of γ-SF with excitation energy and spin of initial states are examined. Deviations from the BAH are discussed and their consequences on the calculations of neutron-capture cross sections (NCCS) are illustrated.

The CI was applied frequently in recent years to study dipole M 1 γ-SF, see e.g. [?, [25][26][27][28]. Here a full 1hω psd -pf model space is used to explore the E1 transitions in neutron-rich Ne isotopes while the M 1 magnetic dipole ones are described within 0hω sd-shell. Selected results are verified extending the calculations to (1 + 3)hω and (0 + 2)hω excitations for E1 and M 1 operators, respectively. The CI Hamiltonian reads:

H = i i c † i c i + ijkl V ijkl c † i c † j c l c k + βH COM (1)
where the center-of-mass (COM) Hamiltonian with a multiplication coefficient β = 10 is added to push up the COM eigenvalues to the energy range not considered here. The isovector E1 transition operator is considered

Ôλ=1 µ = -e Z A N i=1 r i Y 1µ (r i ) + e N A Z i=1 r i Y 1µ (r i ) (2)
substracting the COM motion. In the calculations of M 1 transitions the spin part of the operator is quenched by the usual factor of 0.75, see Ref. [29]. The effective interaction used in this work is the semi-empirical one developed in [30]. To describe photoabsorption, Lanczos Strength Function method [29] with 300 iterations is used. This permits to obtain the strength per energy interval in the whole energy range that can be described in a model space (see as well [31] for recent applications of Lanczos techniques in the context of the BAH for Gamow-Teller transitions). The deexcitation γ-SF are derived from CI results using Bartholomew definition [32], as done previously in [21,28]:

f E1/M 1 (E γ ) = 16π 9(hc) 3 B(E1/M 1; E exc , E γ ) ρ(E exc ) (3)
where E γ is the transition energy, B(E1/M 1; E exc , E γ ) the averaged reduced transition probability at excitation energy E exc and ρ(E exc ) the corresponding level density. Contributions from all the excited states up to 1MeV above the neutron separation energy (S n ) are taken into account in the calculations. The strengths presented in graphs are additionally convoluted with a Lorentzian with an arbitrary width Γ/2 = 500keV. To test the BAH, integrated quantities and the shapes of γ-SF obtained on a number of excited states are analysed. Sum rule of a transition operator (SR), energy-weighted sum rule, centroid and width of the distributions are calculated following Ref. [36]. [33]. γ-SF obtained from CI and available QRPA calculations are employed to compute radiative NCCS within the Hauser-Feshbach model [34] implemented in the TALYS reaction code [35].

In Fig. 1 the sum of E1 strength in the 0-14MeV interval is presented as well as the energy of the first state with transition value to the g.s. B(E1) > 0.01e 2 f m 2 along the Ne chain. There is no E1 strength in this interval in 20 Ne, as expected in a N = Z nucleus, where isospin T= 0 transitions are forbidden. The low-energy strength appears in 22 Ne and continues to augment till the last calculated case. In particular, 26 Ne was shown experimentally to have a pygmy mode: The experimental B(E1) up to 10MeV amounts to 0.49 ± 0.16e 2 f m 2 [24] while the CI value is 0.486e 2 f m 2 and exhausts around 5% of Thomas-Reihe-Kuhn sum rule. All 1 -states computed in the 7-10MeV energy range have wave functions with probabilities of major components not exceeding 10%, suggesting a collective nature of the low-energy strength. The nature of PDR strength in 26 Ne was previously discussed in theory [36,37] and will be adressed within the present approach in a forthcoming publication [38]. QRPA calculations of Ne isotopes from [36] are added for comparison in the Figure :  though there is a qualitative agreement between theoretical calculations, CI gives more strength at low energies, the consequences of which on NCCS calculations will be discussed below.

The major interest of this work is the validity of the BAH, thus the total strengths of E1 and M 1 operators are first investigated for a large number of initial states. In Fig. 2 those are plotted for selected nuclei as function of excitation energy and of initial spin. Both 1hω and 3hω calculations are reported. E1 SR are reduced in 3hω calculations with respect to 1hω but both calculations show a flat behavior. This is in accord with previous CI results from [19] where the E1 SR showed only a weak violation of the BAH. However, a truncated model space used in that work brings a larger spread of SR values when compared to a full 1hω calculation, yielding summation from all the possible 1p-1h excitations. Including 3hω excitations does not change considerably the trend of the SR, a consequence of more than 60% of the wave function residing in the sd-shell model space in low-energy states. The behavior is different for the M 1 operator connecting solely the 0hω (or 2hω) states where interference between components in the ground and excited states lead to alternation of the SR much more sensitive to the initial state structure. As a consequence the M 1 SR do not show the constant tendency with energy/spin (as well in agreement with [19]), independently of the configuration space.

To investigate further the BAH for E1 dipole, strength distributions were explored for a number of excited states in 3 nuclei: i) 22 Ne which was predicted in [36] to have a β = 0.5 deformation and a g.s. distribution with a doublepeak structure, ii) 26 Ne predicted to have a PDR, iii) 27 Ne, an even-odd isotope without a large energy gap in the spectrum and with a PDR strength obtained on the g.s. in CI. Fig. 3 shows the E1 distributions in these nuclei computed for various initial states and their characteristics are listed in Tab. 1. While SR from Fig. 2 are fairly similar, the distributions appear different. Starting with 22 Ne, the asymmetric double-peak structure of the 0 + 1 disappears for higher-energy states. It is known that deformation causes the split of the GDR so the shapes of γ-SF may differ in nuclei where spherical and deformed states coexist. On the other hand, the centroids and widths stay reasonably close, see Tab. 1. The low-energy part shows further devitations which are particularly large for the g. s. as compared to excited states: the transition energy of the lowest 1 -reduces with excitation energy of the initial state due to the availability of many final states at higher energies. The energy-weighted sum of B(E1) (for E γ =0-10MeV) grows with excitation energy due to the same reason. These effects appear common to E1 and to M 1 transitions from previous CI calculations [39,40]. In the temperature-dependent QRPA calculations from [20], the largest deviations from the BAH were also noted at low energy for the g.s. γ-SF.

Moving to 26 Ne, E1 distributions also have similar widths and centroids: the conspicuous deviation concerns the lowest energies where pygmy peaks are visible only for the g.s. Contrary to the 22 Ne case, the energy-weighted sum of B(E1) to E γ =10MeV is the largest for the g.s., due to the presence of a first significant transition at 4.6MeV and a collection of strong transitions around 7-9MeV, well visible as a pygmy peak in Fig. 3. The same effect occurs in 28 Ne and in the even-odd 27 Ne where a clear peak around 7-9MeV can be observed in the g.s. distribution in Fig. 3. In spite of variations noted in the energy-weighted sums, the summed low-energy strength remains similar for various initial states. This is caused by the availability of many opposite parity states in the E γ =0-10MeV interval when increasing excitation energy of the initial state: taking 26 Ne as example, there are 14 1 -states up to 10 MeV above the g.s. but 49 states up to 10 MeV above the 0 + 2 . However, the strongest transition from the g.s. reaches 0.1e 2 f m 2 while from the 0 + 2 maximally 0.04e 2 f m 2 . Transitions connecting 0 + 2 with 1 -states around 8-10 MeV excitation energy are weak, leading to the summed strength of only 0.068e 2 f m 2 , one order of magnitude lower than for the g.s. This difference in magnitude has to be related to the particular structure of initial states: The major com-

ponent in 0 + 1 in 26 Ne is 53% of ν(s 1/2 ) 2 configuration while in 0 + 2 43% of ν(d 3/2 ) 2 .
In 28 Ne, the first 0 + is composed of 78% of ν(s 1/2 ) 2 (d 3/2 ) 2 configuration while the second 0 + has only 31% of the dominant component of the same type. Large contributions to the pygmy peaks related e.g. to ν2s 1/2 → 2p transitions are thus smaller in excited states with respect to the g.s. As building of subsequent excited states requires more and more configuration mixing, the decrease of the PDR strength on excited states obtained here could be expected in other regions of nuclei as well: In [41] a reduction of the PDR strength with temperature was noted in open-shell Ni isotopes in QRPA calculations with Skyrme forces in the temperature range T <1MeV and this due to decreasing pairing correlations.

Table 1. Characteristics of the E1 distributions in selected states and nuclei: transition energy of the first peak with B(E1) > 0.001e 2 f m 2 , centroid, width, sum of strength and of energy-weighted strength in the Eγ=0-10MeV interval. To evaluate the importance of the above-found deviations from the BAH, different microscopic γ-SF were used as input to calculations of NCCS. In Fig. 4 E1 γ-SF of 26 Ne (panel (a)) and the NCCS (panel (b)) of the 25 Ne(n, γ) 26 Ne reaction are shown. First, CI photoabsorption γ-SF on g.s. and a few excited states are used in calculations: the lowest NCCS is obtained with the g.s. γ-SF and is connected to the lack of the low-energy γ-ray transitions when compared to the γ-SF of excited states. The PDR present in the g.s. γ-SF appears to have no influence in the NCCS calculation as the transition energies related to PDR of the order of 7-9MeV are located above neutron thresholds of nuclei studied here: 5.56MeV in 26 Ne, 1.5MeV in 27 Ne and 3.89MeV in 28 Ne. On the contrary, shifting of the γ-strength to lower energies observed for the excited states appears of substantial impact: At incident neutron energy E n = 100keV the differences between theoretical NCCS using the γ-SF of the g.s. and of excited states range from factor 3 for 21 Ne and 25 Ne targets up to 8 for 26 Ne target. Using the QRPA γ-SF from [36] underestimates up to a factor 60 the CI results due to the absence of any transitions below 10MeV, see Fig. 1.

J π i first peak centroid width B(E1) (Eγ • B(E1)) (MeV) (MeV) (MeV) (e 2 f m 2 ) (MeVe 2 f
One should note that computing (n, γ) reaction rates using the microscopic photoabsorption γ-SF requires that photoabsorption and deexcitation strengths are the same. This was shown incorrect in CI calculations [21,39] which inspired low-energy corrections of QRPA γ-SF in [22]. The deexcitation CI γ-SF from Eq. 3 is shown in Fig. 4 as well as the resulting NCCS (results denoted as CI, decay): the difference between deexcitation γ-SF and photoabsorption on the g.s. gives a factor 2 deviation in NCCS at E n = 100keV in the case shown in Fig. 4 and up to a factor 10 difference for the NCCS of the 26 Ne(n, γ) 27 Ne reaction. Empirically modified QRPA γ-SF from Ref. [22] is also displayed: The corresponding NCCS appears to be in fair agreement with the CI contrary to the case of using "bare" QRPA photoabsorption γ-SF from [36].

Once converted to the same units, photoabsorption M 1 γ-SF are an order of magnitude lower than those for E1 and do not influence the computed NCCS. This is however not true for the deexcitation strengths at low γ energies where strong M 1 transitions compete with E1, enhancing further the cross sections with respect to those based on the g.s. photoabsorption γ-SF (see Refs. [25][26][27]21,28] for the low-energy enhancement of M 1 radiation). One can thus conclude that violation of the BAH for dipole transitions at low energies leads systematically to an underestimation of the NCCS computed with the photoabsorption γ-SF of the g.s.

Present results confirm previous, seemingly contradictory theoretical findings: it is verified that the E1 SR remain constant in a large range of excitation energy as found in previous CI studies [19] but the details of γ-SF are different at low energy, with a largest discrepancy for the g.s., in agreement with temperature-dependent QRPA calculations [20]. It is thus confirmed that the BAH may hold for the GDR but not in the low-energy range where the dipole strength is shifted down in γ energy for excited states. The CI deexcitation γ-SF is also shown to be larger than the absorption on the g.s. which leads to lower NCCS computed using the latter. Employing QRPA γ-SF with empirical zero-energy limits leads to a reasonable agreement with calculations using fully microscopic deexcitation γ-SF from the CI in Ne isotopes.

The BAH in the PDR region appears broken in Ne isotopes: The PDR is shown to be the property of the g.s. E1 strength distributions only. Even though the accumulated B(E1) strength per γ-energy interval remains similar for various initial states, large B(E1) transitions around 8-10MeV of excitation energy, characteristic for the PDR, are no longer present in the strength distributions on excited states. The spreading of the low-energy strength in Ne isotopes is understood due to the increased configuration mixing in the excited states on which the resonances are built and as such could be common also to other nuclei with PDR. Temperature-dependent QRPA calculations could be pivotal to probe this behavior in this and other isotopic chains.

Fig. 1 .

 1 Fig. 1. Sum of low-energy E1 strength (upper panel) and energy of the first 1 -state with significative B(E1) transition to the g.s. (lower panel) along the Ne chain. CI results (squares) are compared to QRPA results (open circles) from [36].

Fig. 2 .

 2 Fig. 2. Sum rule (SR) dependence on excitation energies (panels (a) and (b)) and on spins of initial states (panels (c) and (d)) in selected nuclei. The units are (e 2 f m 2 ) for E1 and (µ 2 N ) for M 1 strengths. Both 1hω (bullets) and 3hω (open circles) CI results are reported.

Fig. 4 .

 4 Fig. 4. Panel (a): microscopic E1 dipole γ-SF (fE1) in 26 Ne used in the calculations of neutron capture cross sections (σ) of the 25 Ne(n, γ) 26 Ne reaction shown in panel (b). En stands for the incident neutron energy. Vertical line in panel (a) indicates the neutron separation energy. See text for more details.

Acknowledgments

I am deeply thankful to the late Etienne Caurier, the author of codes ANTOINE and NATHAN, and many other unique nuclear structure tools that were useful in this study. I thank S. Goriely and J. Ljungvall for the careful reading of the manuscript and S. Péru for providing QRPA results. Discussions with S. Goriely are duly acknowledged.