Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes.

Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k-mer read alignment tool. Additionally, we demonstrated that the completeness and diversity of the genomes present in the reference databases are key parameters for accurate and easy interpretation of the sequencing data. Finally, we explored whether KMA, in a two-step procedure, can be used to link the detected AMR genes to their bacterial host chromosome, both detected within the same long-reads. The confidence levels were successfully tested on 28 metagenomics datasets which were obtained with sequencing of real and spiked samples from fecal (chicken, pig, and buffalo) or food (minced beef and food enzyme products) origin. The methodology proposed in this study will facilitate the analysis of metagenomics sequencing datasets for KMA users. Ultimately, this will contribute to improvements in the rapid diagnosis and surveillance of pathogens and AMR genes in food-producing environments, as prioritized by the EU.

A novel metagenomic approach uncovers phage genes as markers for increased disinfectant tolerance in mixed Listeria monocytogenes communities.

Listeria monocytogenes is an important human pathogen with a high mortality rate. Consumption of contaminated ready-to-eat food is the main mode of transmission to humans. Disinfectant-tolerant L. monocytogenes have emerged, which are believed to have increased persistence potential. Elucidating the mechanisms of L. monocytogenes disinfectant tolerance has been the focus of previous studies using pure cultures. A limitation of such approach is the difficulty to identify strains with reduced susceptibility due to inter-strain variation and the need to screen large numbers of strains and genes. In this study, we applied a novel metagenomic approach to detect genes associated with disinfectant tolerance in mixed L. monocytogenes planktonic communities. Two communities, consisting of 71 and 80 isolates each, were treated with the food industry disinfectants benzalkonium chloride (BC, 1.75 mg/L) or peracetic acid (PAA, 38 mg/L). The communities were subjected to metagenomic sequencing and differences in individual gene abundances between biocide-free control communities and biocide-treated communities were determined. A significant increase in the abundance of Listeria phage-associated genes was observed in both communities after treatment, suggesting that prophage carriage could lead to an increased disinfectant tolerance in mixed L. monocytogenes planktonic communities. In contrast, a significant decrease in the abundance of a high-copy emrC-harbouring plasmid pLmN12-0935 was observed in both communities after treatment. In PAA-treated community, a putative ABC transporter previously found to be necessary for L. monocytogenes resistance to antimicrobial agents and virulence, was among the genes with the highest weight for differentiating treated from control samples. The undertaken metagenomic approach in this study can be applied to identify genes associated with increased tolerance to other antimicrobials in mixed bacterial communities.

Ongoing mpox outbreak in Kamituga, South Kivu province, associated with monkeypox virus of a novel Clade I sub-lineage, Democratic Republic of the Congo, 2024.

Since the beginning of 2023, the number of people with suspected monkeypox virus (MPXV) infection have sharply increased in the Democratic Republic of the Congo (DRC). We report near-to-complete MPXV genome sequences derived from six cases from the South Kivu province. Phylogenetic analyses reveal that the MPXV affecting the cases belongs to a novel Clade I sub-lineage. The outbreak strain genome lacks the target sequence of the probe and primers of a commonly used Clade I-specific real-time PCR.

The first complete genome sequence of Staphylococcus aureus ST5477.

This study presents the first complete genome of Staphylococcus aureus ST5477, one of the most common sequence types (ST) from bovine in eastern Africa. The genome consists of a 2,723,132-bp circular chromosome and a 3,044-bp plasmid. This strain was collected in 2017 from cow milk in Tanzania.

Transmission of antimicrobial resistance in the gut microbiome of gregarious cockroaches: the importance of interaction between antibiotic exposed and non-exposed populations.

Antimicrobial resistance (AMR) is a major global health concern, further complicated by its spread via the microbiome bacterial members. While mathematical models discuss AMR transmission through the symbiotic microbiome, experimental studies are scarce. Herein, we used a gregarious cockroach, Pycnoscelus surinamensis, as an in vivo animal model for AMR transmission investigations. We explored whether the effect of antimicrobial treatment is detectable with metagenomic sequencing, and whether AMR genes can be spread and established in unchallenged (not treated with antibiotics) individuals following contact with treated donors, and under various frequencies of interaction. Gut and soil substrate microbiomes were investigated by metagenomic sequencing for bacterial community composition and resistome profiling. We found that tetracycline treatment altered the treated gut microbiome by decreasing bacterial diversity and increasing the abundance of tetracycline resistance genes. Untreated cockroaches that interacted with treated donors also had elevated tetracycline resistance. The levels of resistance differed depending on the magnitude and frequency of donor transfer. Additionally, treated donors showed signs of microbiome recovery due to their interaction with the untreated ones. Similar patterns were also recorded in the soil substrate microbiomes. Our results shed light on how interacting microbiomes facilitate AMR gene transmission to previously unchallenged hosts, a dynamic influenced by the interaction frequencies, using an in vivo model to validate theoretical AMR transmission models.IMPORTANCEAntimicrobial resistance is a rising threat to human and animal health. The spread of resistance through the transmission of the symbiotic gut microbiome is of concern and has been explored in theoretical modeling studies. In this study, we employ gregarious insect populations to examine the emergence and transmission of antimicrobial resistance in vivo and validate modeling hypotheses. We find that antimicrobial treatment increases the levels of resistance in treated populations. Most importantly, we show that resistance increased in untreated populations after interacting with the treated ones. The level of resistance transmission was affected by the magnitude and frequency of population mixing. Our results highlight the importance of microbial transmission in the spread of antimicrobial resistance.

The resistomes of rural and urban pigs and poultry in Ghana.

IMPORTANCE: To the best of our knowledge, this is the first report on the resistomes that are measured using metagenomics in livestock from Sub-Saharan Africa. We find notable differences in the microbiomes between both pigs and poultry, and those also varied markedly compared to similar samples from Europe. However, for both animal species, the same bacterial taxa drove such differences. In pigs and urban free-range poultry, we find a very low abundance of antimicrobial resistance genes (ARGs), whereas rural free-range poultry displayed similarity to the European average, and industrialized poultry exhibited higher levels. These findings show how different African livestock bacterial communities and resistomes are from their European counterparts. They also underscore the importance of continued surveillance and investigation into antimicrobial resistance across diverse ecosystems, contributing significantly to global efforts toward combating the threat of antibiotic resistance.

Distinctive hospital and community resistomes in Scottish urban wastewater: Metagenomics of a paired wastewater sampling design.

The wastewater microbiome contains a multitude of resistant bacteria of human origin, presenting an opportunity for surveillance of resistance in the general population. However, wastewater microbial communities are also influenced by clinical sources, such as hospitals. Identifying signatures of the community and hospital resistome in wastewater is needed for interpretation and risk analysis. In this study, we compare the resistome and microbiome of hospital, community, and mixed municipal wastewater to investigate how and why the composition of these different sites differ. We conducted shotgun metagenomic analysis on wastewater samples from eight wastewater treatment plants (WWTPs), four hospitals, and four community sites in Scotland, using a paired sampling design. Cluster analysis and source attribution random forest models demonstrated that the hospital resistome was distinct from community and WWTP resistomes. Hospital wastewater had a higher abundance and diversity of resistance genes, in keeping with evidence that hospitals act as a reservoir and enricher of resistance. However, this distinctive 'hospital' signature appeared to be weak in the resistome of downstream WWTPs, likely due to dilution. We conclude that hospital and community wastewater resistomes differ, with the hospital wastewater representing a reservoir of patient- and hospital environment-associated bacteria. However, this 'hospital' signature is transient and does not overwhelm the community signature in the resistome of the downstream WWTP influent.

Quantitative PCR versus metagenomics for monitoring antibiotic resistance genes: balancing high sensitivity and broad coverage.

The widespread occurrence of clinically relevant antibiotic resistance within humans, animals, and environment motivates the development of sensitive and accurate detection and quantification methods. Metagenomics and quantitative PCR (qPCR) are amongst the most used approaches. In this study, we aimed to evaluate and compare the performance of these methods to screen antibiotic resistance genes in animal faecal, wastewater, and water samples. Water and wastewater samples were from hospital effluent, different treatment stages of two treatment plants, and of the receiving river at the discharge point. The animal samples were from pig and chicken faeces. Antibiotic resistance gene coverage, sensitivity, and usefulness of the quantitative information were analyzed and discussed. While both methods were able to distinguish the resistome profiles and detect gradient stepwise mixtures of pig and chicken faeces, qPCR presented higher sensitivity for the detection of a few antibiotic resistance genes in water/wastewater. In addition, the comparison of predicted and observed antibiotic resistance gene quantifications unveiled the higher accuracy of qPCR. Metagenomics analyses, while less sensitive, provided a markedly higher coverage of antibiotic resistance genes compared to qPCR. The complementarity of both methods and the importance of selecting the best method according to the study purpose are discussed.

Host innate immune responses and microbiome profile of neonatal calves challenged with Cryptosporidium parvum and the effect of bovine colostrum supplementation.

Introduction: Calves are highly susceptible to gastrointestinal infection with Cryptosporidium parvum (C. parvum), which can result in watery diarrhea and eventually death or impaired development. With little to no effective therapeutics, understanding the host's microbiota and pathogen interaction at the mucosal immune system has been critical to identify and test novel control strategies. Methods: Herein, we used an experimental model of C. parvum challenge in neonatal calves to describe the clinical signs and histological and proteomic profiling of the mucosal innate immunity and microbiota shifts by metagenomics in the ileum and colon during cryptosporidiosis. Also, we investigated the impact of supplemental colostrum feeding on C. parvum infection. Results: We showed that C. parvum challenged calves experienced clinical signs including pyrexia and diarrhea 5 days post challenge. These calves showed ulcerative neutrophil ileitis with a proteomic signature driven by inflammatory effectors, including reactive oxygen species and myeloperoxidases. Colitis was also noticed with an aggravated mucin barrier depletion and incompletely filled goblet cells. The C. parvum challenged calves also displayed a pronounced dysbiosis with a high prevalence of Clostridium species (spp.) and number of exotoxins, adherence factors, and secretion systems related to Clostridium spp. and other enteropathogens, including Campylobacter spp., Escherichia sp., Shigella spp., and Listeria spp. Daily supplementation with a high-quality bovine colostrum product mitigated some of the clinical signs and modulated the gut immune response and concomitant microbiota to a pattern more similar to that of healthy unchallenged calves. Discussion: C. parvum infection in neonatal calves provoked severe diarrheic neutrophilic enterocolitis, perhaps augmented due to the lack of fully developed innate gut defenses. Colostrum supplementation showed limited effect mitigating diarrhea but demonstrated some clinical alleviation and specific modulatory influence on host gut immune responses and concomitant microbiota.

Detection of specific uncultured bacteriophages by fluorescence in situ hybridisation in pig microbiome.

Microbial communities have huge impacts on their ecosystems and local environments spanning from marine and soil communities to the mammalian gut. Bacteriophages (phages) are important drivers of population control and diversity in the community, but our understanding of complex microbial communities is halted by biased detection techniques. Metagenomics have provided a method of novel phage discovery independent of in vitro culturing techniques and have revealed a large proportion of understudied phages. Here, five jumbophage genomes, that were previously assembled in silico from pig faecal metagenomes, are detected and observed directly in their natural environment using a modified phageFISH approach, and combined with methods to decrease bias against large-sized phages (e.g., jumbophages). These phages are uncultured with unknown hosts. The specific phages were detected by PCR and fluorescent in situ hybridisation in their original faecal samples as well as across other faecal samples. Co-localisation of bacterial signals and phage signals allowed detection of the different stages of phage life cycle. All phages displayed examples of early infection, advanced infection, burst, and free phages. To our knowledge, this is the first detection of jumbophages in faeces, which were investigated independently of culture, host identification, and size, and based solely on the genome sequence. This approach opens up opportunities for characterisation of novel in silico phages in vivo from a broad range of gut microbiomes.

Foodborne Pathogen Dynamics in Meat and Meat Analogues Analysed Using Traditional Microbiology and Metagenomic Sequencing.

Meat analogues play an increasing role in meeting global nutritional needs. However, while it is well known that meat possesses inherent characteristics that create favourable conditions for the growth of various pathogenic bacteria, much less is known about meat analogues. This study aimed to compare the growth and survival of Escherichia coli HEHA16, Listeria monocytogenes, Salmonella enterica Typhi, Cronobacter sakazakii, and a cocktail of these bacteria in sterile juices from minced chicken, pig, and beef, as well as pea-based and soy-based minced meat. Traditional microbiology and next-generation sequencing of those metagenomes were employed to analyse the pathogen variability, abundance, and survival after an incubation period. Our findings show that all the meat juices provided favourable conditions for the growth and proliferation of the studied bacteria, with the exception of E. coli HEHA16, which showed lower survival rates in the chicken matrix. Meat analogue juice mainly supported L. monocytogenes survival, with C. sakazakii survival supported to a lesser extent. A correlation was observed between the traditional culturing and metagenomic analysis results, suggesting that further work is needed to compare these technologies in foodborne setups. Our results indicate that plant-based meats could serve as vectors for the transmission of certain, but likely not all, foodborne pathogens, using two accurate detection methods. This warrants the need for additional research to better understand and characterise their safety implications, including their potential association with additional pathogens.

Global Distribution and Diversity of Prevalent Sewage Water Plasmidomes.

Sewage water from around the world contains an abundance of short plasmids, several of which harbor antimicrobial resistance genes (ARGs). The global dynamics of plasmid-derived antimicrobial resistance and functions are only starting to be unveiled. Here, we utilized a previously created data set of 159,332 assumed small plasmids from 24 different global sewage samples. The detailed phylogeny, as well as the interplay between their protein domains, ARGs, and predicted bacterial host genera, were investigated to understand sewage plasmidome dynamics globally. A total of 58,429 circular elements carried genes encoding plasmid-related features, and MASH distance analyses showed a high degree of diversity. A single (yet diverse) cluster of 520 predicted Acinetobacter plasmids was predominant among the European sewage water. Our results suggested a prevalence of plasmid-backbone gene combinations over others. This could be related to selected bacterial genera that act as bacterial hosts. These combinations also mirrored the geographical locations of the sewage samples. Our functional domain network analysis identified three groups of plasmids. However, these backbone domains were not exclusive to any given group, and Acinetobacter was the dominant host genus among the theta-replicating plasmids, which contained a reservoir of the macrolide resistance gene pair msr(E) and mph(E). Macrolide resistance genes were the most common in the sewage plasmidomes and were found in the largest number of unique plasmids. While msr(E) and mph(E) were limited to Acinetobacter, erm(B) was disseminated among a range of Firmicutes plasmids, including Staphylococcus and Streptococcus, highlighting a potential reservoir of antibiotic resistance for these pathogens from around the globe. IMPORTANCE Antimicrobial resistance is a global threat to human health, as it inhibits our ability to treat infectious diseases. This study utilizes sewage water plasmidomes to identify plasmid-derived features and highlights antimicrobial resistance genes, particularly macrolide resistance genes, as abundant in sewage water plasmidomes in Firmicutes and Acinetobacter hosts. The emergence of macrolide resistance in these bacteria suggests that macrolide selective pressure exists in sewage water and that the resident bacteria can readily acquire macrolide resistance via small plasmids.

PlasmidHostFinder: Prediction of Plasmid Hosts Using Random Forest.

Plasmids play a major role facilitating the spread of antimicrobial resistance between bacteria. Understanding the host range and dissemination trajectories of plasmids is critical for surveillance and prevention of antimicrobial resistance. Identification of plasmid host ranges could be improved using automated pattern detection methods compared to homology-based methods due to the diversity and genetic plasticity of plasmids. In this study, we developed a method for predicting the host range of plasmids using machine learning-specifically, random forests. We trained the models with 8,519 plasmids from 359 different bacterial species per taxonomic level; the models achieved Matthews correlation coefficients of 0.662 and 0.867 at the species and order levels, respectively. Our results suggest that despite the diverse nature and genetic plasticity of plasmids, our random forest model can accurately distinguish between plasmid hosts. This tool is available online through the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/PlasmidHostFinder/). IMPORTANCE Antimicrobial resistance is a global health threat to humans and animals, causing high mortality and morbidity while effectively ending decades of success in fighting against bacterial infections. Plasmids confer extra genetic capabilities to the host organisms through accessory genes that can encode antimicrobial resistance and virulence. In addition to lateral inheritance, plasmids can be transferred horizontally between bacterial taxa. Therefore, detection of the host range of plasmids is crucial for understanding and predicting the dissemination trajectories of extrachromosomal genes and bacterial evolution as well as taking effective countermeasures against antimicrobial resistance.

FI: The Fecobiome Initiative.

Animal husbandry has been key to the sustainability of human societies for millennia. Livestock animals, such as cattle, convert plants to protein biomass due to a compartmentalized gastrointestinal tract (GIT) and the complementary contributions of a diverse GIT microbiota, thereby providing humans with meat and dairy products. Research on cattle gut microbial symbionts has mainly focused on the rumen (which is the primary fermentation compartment) and there is a paucity of functional insight on the intestinal (distal end) microbiota, where most foodborne zoonotic bacteria reside. Here, we present the Fecobiome Initiative (or FI), an international effort that aims at facilitating collaboration on research projects related to the intestinal microbiota, disseminating research results, and increasing public availability of resources. By doing so, the FI can help mitigate foodborne and animal pathogens that threaten livestock and human health, reduce the emergence and spread of antimicrobial resistance in cattle and their proximate environment, and potentially improve the welfare and nutrition of animals. We invite all researchers interested in this type of research to join the FI through our website: www.fecobiome.com.

A Peek into the Plasmidome of Global Sewage.

Plasmids can provide a selective advantage for microorganisms to survive and adapt to new environmental conditions. Plasmid-encoded traits, such as antimicrobial resistance (AMR) or virulence, impact the ecology and evolution of bacteria and can significantly influence the burden of infectious diseases. Insight about the identity and functions encoded on plasmids on the global scale are largely lacking. Here, we investigate the plasmidome of 24 samples (22 countries, 5 continents) from the global sewage surveillance project. We obtained 105-Gbp Oxford Nanopore and 167-Gbp Illumina NextSeq DNA sequences from plasmid DNA preparations and assembled 165,302 contigs (159,322 circular). Of these, 58,429 carried genes encoding for plasmid-related and 11,222 for virus/phage-related proteins. About 90% of the circular DNA elements did not have any similarity to known plasmids. Those that exhibited similarity had similarity to plasmids whose hosts were previously detected in these sewage samples (e.g., Acinetobacter, Escherichia, Moraxella, Enterobacter, Bacteroides, and Klebsiella). Some AMR classes were detected at a higher abundance in plasmidomes (e.g., macrolide-lincosamide-streptogramin B, macrolide, and quinolone) compared to the respective complex sewage samples. In addition to AMR genes, a range of functions were encoded on the candidate plasmids, including plasmid replication and maintenance, mobilization, and conjugation. In summary, we describe a laboratory and bioinformatics workflow for the recovery of plasmids and other potential extrachromosomal DNA elements from complex microbiomes. Moreover, the obtained data could provide further valuable insight into the ecology and evolution of microbiomes, knowledge about AMR transmission, and the discovery of novel functions. IMPORTANCE This is, to the best of our knowledge, the first study to investigate plasmidomes at a global scale using long read sequencing from complex untreated domestic sewage. Previous metagenomic surveys have detected AMR genes in a variety of environments, including sewage. However, it is unknown whether the AMR genes were present on the microbial chromosome or located on extrachromosomal elements, such as plasmids. Using our approach, we recovered a large number of plasmids, of which most appear novel. We identified distinct AMR genes that were preferentially located on plasmids, potentially contributing to their transmissibility. Overall, plasmids are of great importance for the biology of microorganisms in their natural environments (free-living and host-associated), as well as for molecular biology and biotechnology. Plasmidome collections may therefore be valuable resources for the discovery of fundamental biological mechanisms and novel functions useful in a variety of contexts.

Outcome of Different Sequencing and Assembly Approaches on the Detection of Plasmids and Localization of Antimicrobial Resistance Genes in Commensal Escherichia coli.

Antimicrobial resistance (AMR) is a major threat to public health worldwide. Currently, AMR typing changes from phenotypic testing to whole-genome sequence (WGS)-based detection of resistance determinants for a better understanding of the isolate diversity and elements involved in gene transmission (e.g., plasmids, bacteriophages, transposons). However, the use of WGS data in monitoring purposes requires suitable techniques, standardized parameters and approved guidelines for reliable AMR gene detection and prediction of their association with mobile genetic elements (plasmids). In this study, different sequencing and assembly strategies were tested for their suitability in AMR monitoring in Escherichia coli in the routines of the German National Reference Laboratory for Antimicrobial Resistances. To assess the outcomes of the different approaches, results from in silico predictions were compared with conventional phenotypic- and genotypic-typing data. With the focus on (fluoro)quinolone-resistant E.coli, five qnrS-positive isolates with multiple extrachromosomal elements were subjected to WGS with NextSeq (Illumina), PacBio (Pacific BioSciences) and ONT (Oxford Nanopore) for in depth characterization of the qnrS1-carrying plasmids. Raw reads from short- and long-read sequencing were assembled individually by Unicycler or Flye or a combination of both (hybrid assembly). The generated contigs were subjected to bioinformatics analysis. Based on the generated data, assembly of long-read sequences are error prone and can yield in a loss of small plasmid genomes. In contrast, short-read sequencing was shown to be insufficient for the prediction of a linkage of AMR genes (e.g., qnrS1) to specific plasmid sequences. Furthermore, short-read sequencing failed to detect certain duplications and was unsuitable for genome finishing. Overall, the hybrid assembly led to the most comprehensive typing results, especially in predicting associations of AMR genes and mobile genetic elements. Thus, the use of different sequencing technologies and hybrid assemblies currently represents the best approach for reliable AMR typing and risk assessment.

Evaluating the usefulness of next-generation sequencing for herb authentication.

Food authentication is a rapidly growing field driven by increasing public awareness of food quality and safety. Foods containing herbs are particularly prone to industrial fraud and adulteration. Several methodologies are currently used to evaluate food authenticity. DNA-based technologies have increased focus, with DNA barcoding the most widely used. DNA barcoding is based on the sequencing and comparison of orthologous DNA regions from all species in a sample, but the approach is limited by its low resolution to distinguish closely-related species. Here we developed a customised database and bioinformatics pipeline (Herbs Authenticity - GitHub) to identify herbal ingredients implemented as a metagenomics approach for plant-derived product authenticity testing. We evaluated the accuracy of the method by using publicly available plant genomes and databases to allow the construction of our customised database barcodes, which were also complemented with entries from publicly available resources (iBOL and ENA). The pipeline performance was then tested with new 47 de novo partly sequenced whole plant genomes or barcodes as query sequences. Our results show that using our mapping algorithm with the customised barcode database correctly identifies the main components of a wide range of plant-derived samples, albeit with variable additional noise across samples depending on the tested samples and barcodes. Our result also show that at the current stage the usefulness of metagenomics is limited by the availability of reference sequences and the needed sequencing depth. However, this method shows promise for evaluating the authenticity of different herbal products provided that the method is further refined to increase the qualitative and quantitative accuracy.

Disease-free monoculture farming by fungus-growing termites.

Fungus-growing termites engage in an obligate mutualistic relationship with Termitomyces fungi, which they maintain in monocultures on specialised fungus comb structures, without apparent problems with infectious diseases. While other fungi have been reported in the symbiosis, detailed comb fungal community analyses have been lacking. Here we use culture-dependent and -independent methods to characterise fungus comb mycobiotas from three fungus-growing termite species (two genera). Internal Transcribed Spacer (ITS) gene analyses using 454 pyrosequencing and Illumina MiSeq showed that non-Termitomyces fungi were essentially absent in fungus combs, and that Termitomyces fungal crops are maintained in monocultures as heterokaryons with two or three abundant ITS variants in a single fungal strain. To explore whether the essential absence of other fungi within fungus combs is potentially due to the production of antifungal metabolites by Termitomyces or comb bacteria, we performed in vitro assays and found that both Termitomyces and chemical extracts of fungus comb material can inhibit potential fungal antagonists. Chemical analyses of fungus comb material point to a highly complex metabolome, including compounds with the potential to play roles in mediating these contaminant-free farming conditions in the termite symbiosis.

Gut microbial compositions mirror caste-specific diets in a major lineage of social insects.

Social insects owe their ecological success to the division of labour between castes, but associations between microbial community compositions and castes with different tasks and diets have not been extensively explored. Fungus-growing termites associate with fungi to degrade plant material, complemented by diverse gut microbial communities. Here, we explore whether division of labour and accompanying dietary differences between fungus-growing termite castes are linked to gut bacterial community structure. Using amplicon sequencing, we characterize community compositions in sterile (worker and soldier) and reproductive (queen and king) termites and combine this with gut enzyme activities and microscopy to hypothesise sterile caste-specific microbiota roles. Gut bacterial communities are structured primarily according to termite caste and genus and, in contrast to the observed rich and diverse sterile caste microbiotas, royal pair guts are dominated by few bacterial taxa, potentially reflecting their specialized uniform diet and unique lifestyle.

Hemimetabolous genomes reveal molecular basis of termite eusociality.

Around 150 million years ago, eusocial termites evolved from within the cockroaches, 50 million years before eusocial Hymenoptera, such as bees and ants, appeared. Here, we report the 2-Gb genome of the German cockroach, Blattella germanica, and the 1.3-Gb genome of the drywood termite Cryptotermes secundus. We show evolutionary signatures of termite eusociality by comparing the genomes and transcriptomes of three termites and the cockroach against the background of 16 other eusocial and non-eusocial insects. Dramatic adaptive changes in genes underlying the production and perception of pheromones confirm the importance of chemical communication in the termites. These are accompanied by major changes in gene regulation and the molecular evolution of caste determination. Many of these results parallel molecular mechanisms of eusocial evolution in Hymenoptera. However, the specific solutions are remarkably different, thus revealing a striking case of convergence in one of the major evolutionary transitions in biological complexity.