Estimating the size of the bacterial pan-genome

Meiosis as a mechanism for epigenetic reprogramming and cellular rejuvenation

Meiosis is a hallmark of sexual reproduction because it represents the transition from one life cycle to the next and, in animals, meiosis produces gametes. Why meiosis evolved has been debated and most studies have focused on recombination of the parental alleles as the main function of meiosis. However, 40 years ago, Robin Holliday proposed that an essential function of meiosis is to oppose the consequence of successive mitoses that cause cellular aging. Cellular aging results from accumulated defective organelles and proteins and modifications of chromatin in the form of DNA methylation and histone modifications referred to collectively as epigenetic marks. Here, recent findings supporting the hypothesis that meiosis opposes cellular aging are reviewed and placed in the context of the diversity of the life cycles of eukaryotes, including animals, yeast, flowering plants and the bryophyte Marchantia.

Unveiling the Brazilian kefir microbiome: discovery of a novel Lactobacillus kefiranofaciens (LkefirU) genome and in silico prospection of bioactive peptides with potential anti-Alzheimer properties

BACKGROUND

Kefir is a complex microbial community that plays a critical role in the fermentation and production of bioactive peptides, and has health-improving properties. The composition of kefir can vary by geographic localization and weather, and this paper focuses on a Brazilian sample and continues previous work that has successful anti-Alzheimer properties. In this study, we employed shotgun metagenomics and peptidomics approaches to characterize Brazilian kefir further.

RESULTS

We successfully assembled the novel genome of Lactobacillus kefiranofaciens (LkefirU) and conducted a comprehensive pangenome analysis to compare it with other strains. Furthermore, we performed a peptidome analysis, revealing the presence of bioactive peptides encrypted by L. kefiranofaciens in the Brazilian kefir sample, and utilized in silico prospecting and molecular docking techniques to identify potential anti-Alzheimer peptides, targeting β-amyloid (fibril and plaque), BACE, and acetylcholinesterase. Through this analysis, we identified two peptides that show promise as compounds with anti-Alzheimer properties.

CONCLUSIONS

These findings not only provide insights into the genome of L. kefiranofaciens but also serve as a promising prototype for the development of novel anti-Alzheimer compounds derived from Brazilian kefir.

Step-by-Step Metagenomics for Food Microbiome Analysis: A Detailed Review

This review article offers a comprehensive overview of the current understanding of using metagenomic tools in food microbiome research. It covers the scientific foundation and practical application of genetic analysis techniques for microbial material from food, including bioinformatic analysis and data interpretation. The method discussed in the article for analyzing microorganisms in food without traditional culture methods is known as food metagenomics. This approach, along with other omics technologies such as nutrigenomics, proteomics, metabolomics, and transcriptomics, collectively forms the field of foodomics. Food metagenomics allows swift and thorough examination of bacteria and potential metabolic pathways by utilizing foodomic databases. Despite its established scientific basis and available bioinformatics resources, the research approach of food metagenomics outlined in the article is not yet widely implemented in industry. The authors believe that the integration of next-generation sequencing (NGS) with rapidly advancing digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data will facilitate the widespread adoption of this research strategy in microbial analysis for the food industry. This adoption is expected to enhance food safety and product quality in the near future.

Annotation of 2,507 Saccharomyces cerevisiae genomes

Saccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Currently, a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain. However, these genomes are distributed at different websites and a large number of them are released without annotation information. To provide one complete annotated genome data resource, we collected 2,507 Saccharomyces cerevisiae genome assemblies and re-annotated 2,506 assemblies using a custom annotation pipeline, producing a total of 15,407,164 protein-coding gene models. With a custom pipeline, all these gene sequences were clustered into families. A total of 1,506 single-copy genes were selected as marker genes, which were then used to evaluate the genome completeness and base qualities of all assemblies. Pangenomic analyses were performed based on a selected subset of 847 medium-high-quality genomes. Statistical comparisons revealed a number of gene families showing copy number variations among different organism sources. To the authors' knowledge, this study represents the largest genome annotation project of S. cerevisiae so far, providing rich genomic resources for the future studies of the model organism S. cerevisiae and its relatives.IMPORTANCESaccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Though a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain, these genomes are distributed at different websites and most are released without annotation, hindering the efficient reuse of these genome resources. Here, we collected 2,507 genomes for Saccharomyces cerevisiae, performed genome annotation, and evaluated the genome qualities. All the obtained data have been deposited at public repositories and are freely accessible to the community. This study represents the largest genome annotation project of S. cerevisiae so far, providing one complete annotated genome data set for S. cerevisiae, an important workhorse for fundamental biology, biotechnology, and industry.

Discovery and development of COVID-19 vaccine from laboratory to clinic

The world has recently experienced one of the biggest and most severe public health disasters with severe acute respiratory syndrome coronavirus (SARS-CoV-2). SARS-CoV-2 is responsible for the coronavirus disease of 2019 (COVID-19) which is one of the most widespread and powerful infections affecting human lungs. Current figures show that the epidemic had reached 216 nations, where it had killed about 6,438,926 individuals and infected 590,405,710. WHO proclaimed the outbreak of the Ebola virus disease (EVD), in 2014 that killed hundreds of people in West Africa. The development of vaccines for SARS-CoV-2 becomes more difficult due to the viral mutation in its non-structural proteins (NSPs) especially NSP2 and NSP3, S protein, and RNA-dependent RNA polymerase (RdRp). Continuous monitoring of SARS-CoV-2, dynamics of the genomic sequence, and spike protein mutations are very important for the successful development of vaccines with good efficacy. Hence, the vaccine development for SARS-CoV-2 faces specific challenges starting from viral mutation. The requirement of long-term immunity development, safety, efficacy, stability, vaccine allocation, distribution, and finally, its cost is discussed in detail. Currently, 169 vaccines are in the clinical development stage, while 198 vaccines are in the preclinical development stage. The majority of these vaccines belong to the Ps-Protein subunit type which has 54, and the minor BacAg-SPV (Bacterial antigen-spore expression vector) type, at least 1 vaccination. The use of computational methods and models for vaccine development has revolutionized the traditional methods of vaccine development. Further, this updated review highlights the upcoming vaccine development strategies in response to the current pandemic and post-pandemic era, in the field of vaccine development.

Scaling of Protein Function across the Tree of Life

Scaling laws are a powerful way to compare genomes because they put all organisms onto a single curve and reveal nontrivial generalities as genomes change in size. The abundance of functional categories across genomes has previously been found to show power law scaling with respect to the total number of functional categories, suggesting that universal constraints shape genomic category abundance. Here, we look across the tree of life to understand how genome evolution may be related to functional scaling. We revisit previous observations of functional genome scaling with an expanded taxonomy by analyzing 3,726 bacterial, 220 archaeal, and 79 unicellular eukaryotic genomes. We find that for some functional classes, scaling is best described by multiple exponents, revealing previously unobserved shifts in scaling as genome-encoded protein annotations increase or decrease. Furthermore, we find that scaling varies between phyletic groups at both the domain and phyla levels and is less universal than previously thought. This variability in functional scaling is not related to taxonomic phylogeny resolved at the phyla level, suggesting that differences in cell plan or physiology outweigh broad patterns of taxonomic evolution. Since genomes are maintained and replicated by the functional proteins encoded by them, these results point to functional degeneracy between taxonomic groups and unique evolutionary trajectories toward these. We also find that individual phyla frequently span scaling exponents of functional classes, revealing that individual clades can move across scaling exponents. Together, our results reveal unique shifts in functions across the tree of life and highlight that as genomes grow or shrink, proteins of various functions may be added or lost.

Complete genome sequence and comparative analysis of a Vibrio vulnificus strain isolated from a clinical patient

Vibrio vulnificus is an opportunistic, global pathogen that naturally inhabits sea water and is responsible for most vibriosis-related deaths. We investigated the genetic characteristics of V. vulnificus isolated from the clinical blood culture specimen of a patient with hepatitis B virus cirrhosis in 2018 (named as V. vulnificus VV2018) by whole genome sequencing (WGS). VV2018 belonged to a novel sequencing type 620 (ST620) and comprised two circular chromosomes, containing 4,389 potential coding sequences (CDSs) and 152 RNA genes. The phylogenetic tree of single nucleotide polymorphisms (SNPs) using 26 representative genomes revealed that VV2108 grouped with two other V. vulnificus strains isolated from humans. The pan-genome of V. vulnificus was constructed using 26 representative genomes to elucidate their genetic diversity, evolutionary characteristics, and virulence and antibiotic resistance profiles. The pan-genome analysis revealed that VV2018 shared a total of 3,016 core genes (≥99% presence), including 115 core virulence factors (VFs) and 5 core antibiotic resistance-related genes, and 309 soft core genes (≥95 and <99% presence) with 25 other V. vulnificus strains. The varG gene might account for the cefazolin resistance, and comparative analysis of the genetic context of varG revealed that two genes upstream and downstream of varG were conserved. The glycosylation (pgl) like genes were found in VV2018 compared with Pgl-related proteins in Neisseria that might affect the adherence of the strain in hosts. The comparative analysis of VV2018 would contribute to a better understanding of the virulence and antibiotic resistance profiles of V. vulnificus. Meanwhile much work remains to be done to better understand the function of pgl-like genes in V. vulnificus.

Acquisition of Type I methyltransferase via horizontal gene transfer increases the drug resistance of Aeromonas veronii

Aeromonas veronii is an opportunistic pathogen that affects both fish and mammals, including humans, leading to bacteraemia, sepsis, meningitis and even death. The increasing virulence and drug resistance of A. veronii are of significant concern and pose a severe risk to public safety. The Type I restriction-modification (RM) system, which functions as a bacterial defence mechanism, can influence gene expression through DNA methylation. However, little research has been conducted to explore its origin, evolutionary path, and relationship to virulence and drug resistance in A. veronii. In this study, we analysed the pan-genome of 233 A. veronii strains, and the results indicated that it was 'open', meaning that A. veronii has acquired additional genes from other species. This suggested that A. veronii had the potential to adapt and evolve rapidly, which might have contributed to its drug resistance. One Type I methyltransferase (MTase) and two complete Type I RM systems were identified, namely AveC4I, AveC4II and AveC4III in A. veronii strain C4, respectively. Notably, AveC4I was exclusive to A. veronii C4. Phylogenetic analysis revealed that AveC4I was derived from horizontal gene transfer from Thiocystis violascens and exchanged genes with the human pathogen Comamonas kerstersii. Single molecule real-time sequencing was applied to identify the motif methylated by AveC4I, which was unique and not recognized by any reported MTases in the REBASE database. We also annotated the functions and pathways of the genes containing the motif, revealing that AveC4I may control drug resistance in A. veronii C4. Our findings provide new insight on the mechanisms underlying drug resistance in pathogenic bacteria. By identifying the specific genes and pathways affected by AveC4I, this study may aid in the development of new therapeutic approaches to combat A. veronii infections.

Dynamics of nucleic acid mobility

Advances in sequencing technologies and bioinformatic analyses are accelerating the quantity and quality of data from all domains of life. This rich resource has the potential to reveal a number of important incidences with respect to possible exchange of nucleic acids. Ancient events have impacted species evolution and adaptation to new ecological niches. However, we still lack a full picture of processes ongoing within and between somatic cells, gametes, and different organisms. We propose that events linked to acceptance of alien nucleic acids grossly could be divided into 2 main routes in plants: one, when plants are exposed to extreme challenges and, the second level, a more everyday or season-related stress incited by biotic or abiotic factors. Here, many events seem to comprise somatic cells. Are the transport and acceptance processes of alien sequences random or are there specific regulatory systems not yet fully understood? Following entrance into a new cell, a number of intracellular processes leading to chromosomal integration and function are required. Modification of nucleic acids and possibly exchange of sequences within a cell may also occur. Such fine-tune events are most likely very common. There are multiple questions that we will discuss concerning different types of vesicles and their roles in nucleic acid transport and possible intracellular sequence exchange between species.

Under-Appreciated Phylogroup Diversity of Escherichia coli within and between Animals at the Urban-Wildland Interface

Wild animals have been implicated as reservoirs and even "melting pots" of pathogenic and antimicrobial-resistant bacteria of concern to human health. Though Escherichia coli is common among vertebrate guts and plays a role in the propagation of such genetic information, few studies have explored its diversity beyond humans nor the ecological factors that influence its diversity and distribution in wild animals. We characterized an average of 20 E. coli isolates per scat sample (n = 84) from a community of 14 wild and 3 domestic species. The phylogeny of E. coli comprises 8 phylogroups that are differentially associated with pathogenicity and antibiotic resistance, and we uncovered all of them in one small biological preserve surrounded by intense human activity. Challenging previous assumptions that a single isolate is representative of within-host phylogroup diversity, 57% of individual animals sampled carried multiple phylogroups simultaneously. Host species' phylogroup richness saturated at different levels across species and encapsulated vast within-sample and within-species variation, indicating that distribution patterns are influenced both by isolation source and laboratory sampling depth. Using ecological methods that ensure statistical relevance, we identify trends in phylogroup prevalence associated with host and environmental factors. The vast genetic diversity and broad distribution of E. coli in wildlife populations has implications for biodiversity conservation, agriculture, and public health, as well as for gauging unknown risks at the urban-wildland interface. We propose critical directions for future studies of the "wild side" of E. coli that will expand our understanding of its ecology and evolution beyond the human environment. IMPORTANCE To our knowledge, neither the phylogroup diversity of E. coli within individual wild animals nor that within an interacting multispecies community have previously been assessed. In doing so, we uncovered the globally known phylogroup diversity from an animal community on a preserve imbedded in a human-dominated landscape. We revealed that the phylogroup composition in domestic animals differed greatly from that in their wild counterparts, implying potential human impacts on the domestic animal gut. Significantly, many wild individuals hosted multiple phylogroups simultaneously, indicating the potential for strain-mixing and zoonotic spillback, especially as human encroachment into wildlands increases in the Anthropocene. We reason that due to extensive anthropogenic environmental contamination, wildlife is increasingly exposed to our waste, including E. coli and antibiotics. The gaps in the ecological and evolutionary understanding of E. coli thus necessitate a significant uptick in research to better understand human impacts on wildlife and the risk for zoonotic pathogen emergence.

A review of the pangenome: how it affects our understanding of genomic variation, selection and breeding in domestic animals?

As large-scale genomic studies have progressed, it has been revealed that a single reference genome pattern cannot represent genetic diversity at the species level. While domestic animals tend to have complex routes of origin and migration, suggesting a possible omission of some population-specific sequences in the current reference genome. Conversely, the pangenome is a collection of all DNA sequences of a species that contains sequences shared by all individuals (core genome) and is also able to display sequence information unique to each individual (variable genome). The progress of pangenome research in humans, plants and domestic animals has proved that the missing genetic components and the identification of large structural variants (SVs) can be explored through pangenomic studies. Many individual specific sequences have been shown to be related to biological adaptability, phenotype and important economic traits. The maturity of technologies and methods such as third-generation sequencing, Telomere-to-telomere genomes, graphic genomes, and reference-free assembly will further promote the development of pangenome. In the future, pangenome combined with long-read data and multi-omics will help to resolve large SVs and their relationship with the main economic traits of interest in domesticated animals, providing better insights into animal domestication, evolution and breeding. In this review, we mainly discuss how pangenome analysis reveals genetic variations in domestic animals (sheep, cattle, pigs, chickens) and their impacts on phenotypes and how this can contribute to the understanding of species diversity. Additionally, we also go through potential issues and the future perspectives of pangenome research in livestock and poultry.

Genetic Determinants of Escherichia coli Survival in Beach Sand

Escherichia coli contain a high level of genetic diversity and are generally associated with the guts of warm-blooded animals but have also been isolated from secondary habitats outside hosts. We used E. coli isolates from previous in situ microcosm experiments conducted under actual beach conditions and performed population-level genomic analysis to identify accessory genes associated with survival within the beach sand environment. E. coli strains capable of surviving had been selected for by seeding isolates originating from sand, sewage, and gull waste (n = 528; 176 from each source) into sand, which was sealed in microcosm chambers and buried for 45 days in the backshore beach of Lake Michigan. In the current work, survival-associated genes were identified by comparing the pangenome of viable E. coli populations at the end of the microcosm experiment with the original isolate collection and identifying loci enriched in the out put samples. We found that environmental survival was associated with a wide variety of genetic factors, with the majority corresponding to metabolism enzymes and transport proteins. Of the 414 unique functions identified, most were present across E. coli phylogroups, except B2 which is often associated with human pathogens. Gene modules that were enriched in surviving populations included a betaine biosynthesis pathway, which produces an osmoprotectant, and the GABA (gamma-aminobutyrate) biosynthesis pathway, which aids in pH homeostasis and nutrient use versatility. Overall, these results demonstrate that the genetic flexibility within this species allows for survival in the environment for extended periods. IMPORTANCE Escherichia coli is commonly used as an indicator of recent fecal pollution in recreational water despite its known ability to survive in secondary environments, such as beach sand. These long-term survivors from sand reservoirs can be introduced into the water column through wave action or runoff during precipitation events, thereby impacting the perception of local water quality. Current beach monitoring methods cannot differentiate long-term environmental survivors from E. coli derived from recent fecal input, resulting in inaccurate monitoring results and unnecessary beach closures. This work identified the genetic factors that are associated with long-term survivors, providing insight into the mechanistic basis for E. coli accumulation in beach sand. A greater understanding of the intrinsic ability of E. coli to survive long-term and conditions that promote such survival will provide evidence of the limitations of beach water quality assessments using this indicator.

Very early evolution from the perspective of microbial ecology

The universal ancestor at the root of the species tree of life depicts a population of organisms with a surprising degree of complexity, posessing genomes and translation systems much like that of microbial life today. As the first life forms were most likely to have been simple replicators, considerable evolutionary change must have taken place prior to the last universal common ancestor. It is often assumed that the lack of earlier branches on the tree of life is due to a prevalence of random horizontal gene transfer that obscured the delineations between lineages and hindered their divergence. Therefore, principles of microbial evolution and ecology may give us some insight into these early stages in the history of life. Here, we synthesize the current understanding of organismal and genome evolution from the perspective of microbial ecology and apply these evolutionary principles to the earliest stages of life on Earth. We focus especially on broad evolutionary modes pertaining to horizontal gene transfer, pangenome structure, and microbial mat communities.

Genomes of Vibrio metoecus co-isolated with Vibrio cholerae extend our understanding of differences between these closely related species

BACKGROUND

Vibrio cholerae, the causative agent of cholera, is a well-studied species, whereas Vibrio metoecus is a recently described close relative that is also associated with human infections. The availability of V. metoecus genomes provides further insight into its genetic differences from V. cholerae. Additionally, both species have been co-isolated from a cholera-free brackish coastal pond and have been suggested to interact with each other by horizontal gene transfer (HGT).

RESULTS

The genomes of 17 strains from each species were sequenced. All strains share a large core genome (2675 gene families) and very few genes are unique to each species (< 3% of the pan-genome of both species). This led to the identification of potential molecular markers-for nitrite reduction, as well as peptidase and rhodanese activities-to further distinguish V. metoecus from V. cholerae. Interspecies HGT events were inferred in 21% of the core genes and 45% of the accessory genes. A directional bias in gene transfer events was found in the core genome, where V. metoecus was a recipient of three times (75%) more genes from V. cholerae than it was a donor (25%).

CONCLUSION

V. metoecus was misclassified as an atypical variant of V. cholerae due to their resemblance in a majority of biochemical characteristics. More distinguishing phenotypic assays can be developed based on the discovery of potential gene markers to avoid any future misclassifications. Furthermore, differences in relative abundance or seasonality were observed between the species and could contribute to the bias in directionality of HGT.

Pan-Genome Analysis of Campylobacter: Insights on the Genomic Diversity and Virulence Profile

The genus Campylobacter contains pathogens that cause bacterial gastroenteritis in humans and animals. Despite large-scale sequencing efforts to raise clinical awareness of Campylobacter, little is known about the diversity and functions of virulence factors. Here, we constructed the pan-genome of Campylobacter using 39 representative genomes, elucidating their genetic diversity, evolutionary characteristics, and virulence and resistance profiles. The Campylobacter pan-genome was open and showed extensive genome variability, with high levels of gene expansion and contraction as the organism evolved. These Campylobacter members had diverse virulence gene content, and six potential core virulence genes (porA, PEB4, cheY, htrB, Cj1135, and kpsF) have been identified. The conserved mechanisms for Campylobacter pathogenicity were related to adherence, motility, and immune modulation. We emphasized the relative importance of variable virulence genes. Many virulence genes have experienced expansion or contraction in specific lineages, which may be one of the factors causing differences in the content of virulence genes. Additionally, these Campylobacter genomes have a high prevalence of the cmeA and cmeC genes, which are linked to the CmeABC pump and contribute to multidrug resistance. The genomic variations, core and variable virulence factors, and resistance genes of Campylobacter characterized in this study would contribute to a better understanding of the virulence of Campylobacter and more effective use of candidates for drug development and prevention of Campylobacter infections. IMPORTANCE Pathogenic members of the genus Campylobacter are recognized as one of the major causative agents of human bacterial gastroenteritis. This study revealed the pan-genome of 39 Campylobacter species, provided the most updated reconstruction of the global virulence gene pool of 39 Campylobacter species, and identified species-related virulence differences. This study highlighted the basic conserved functionality and specificity of pathogenicity that are crucial to infection, which was critical for improving the diagnosis and prevention of Campylobacter infections.

Multiple genome alignment in the telomere-to-telomere assembly era

With the arrival of telomere-to-telomere (T2T) assemblies of the human genome comes the computational challenge of efficiently and accurately constructing multiple genome alignments at an unprecedented scale. By identifying nucleotides across genomes which share a common ancestor, multiple genome alignments commonly serve as the bedrock for comparative genomics studies. In this review, we provide an overview of the algorithmic template that most multiple genome alignment methods follow. We also discuss prospective areas of improvement of multiple genome alignment for keeping up with continuously arriving high-quality T2T assembled genomes and for unlocking clinically-relevant insights.

De Novo Long-Read Whole-Genome Assemblies and the Comparative Pan-Genome Analysis of Ascochyta Blight Pathogens Affecting Field Pea

Ascochyta Blight (AB) is a major disease of many cool-season legumes globally. In field pea, three fungal pathogens have been identified to be responsible for this disease in Australia, namely Peyronellaea pinodes, Peyronellaea pinodella and Phoma koolunga. Limited genomic resources for these pathogens have been generated, which has hampered the implementation of effective management strategies and breeding for resistant cultivars. Using Oxford Nanopore long-read sequencing, we report the first high-quality, fully annotated, near-chromosome-level nuclear and mitochondrial genome assemblies for 18 isolates from the Australian AB complex. Comparative genome analysis was performed to elucidate the differences and similarities between species and isolates using phylogenetic relationships and functional diversity. Our data indicated that P. pinodella and P. koolunga are heterothallic, while P. pinodes is homothallic. More homology and orthologous gene clusters are shared between P. pinodes and P. pinodella compared to P. koolunga. The analysis of the repetitive DNA content showed differences in the transposable repeat composition in the genomes and their expression in the transcriptomes. Significant repeat expansion in P. koolunga's genome was seen, with strong repeat-induced point mutation (RIP) activity being evident. Phylogenetic analysis revealed that genetic diversity can be exploited for species marker development. This study provided the much-needed genetic resources and characterization of the AB species to further drive research in key areas such as disease epidemiology and host-pathogen interactions.

High-quality pan-genome of Escherichia coli generated by excluding confounding and highly similar strains reveals an association between unique gene clusters and genomic islands

The pan-genome analysis of bacteria provides detailed insight into the diversity and evolution of a bacterial population. However, the genomes involved in the pan-genome analysis should be checked carefully, as the inclusion of confounding strains would have unfavorable effects on the identification of core genes, and the highly similar strains could bias the results of the pan-genome state (open versus closed). In this study, we found that the inclusion of highly similar strains also affects the results of unique genes in pan-genome analysis, which leads to a significant underestimation of the number of unique genes in the pan-genome. Therefore, these strains should be excluded from pan-genome analysis at the early stage of data processing. Currently, tens of thousands of genomes have been sequenced for Escherichia coli, which provides an unprecedented opportunity as well as a challenge for pan-genome analysis of this classical model organism. Using the proposed strategies, a high-quality E. coli pan-genome was obtained, and the unique genes was extracted and analyzed, revealing an association between the unique gene clusters and genomic islands from a pan-genome perspective, which may facilitate the identification of genomic islands.

A genome-wide scan of wastewater E. coli for genes under positive selection: focusing on mechanisms of antibiotic resistance

Antibiotic resistance is a global health threat and consequently, there is a need to understand the mechanisms driving its emergence. Here, we hypothesize that genes and mutations under positive selection may contribute to antibiotic resistance. We explored wastewater E. coli, whose genomes are highly diverse. We subjected 92 genomes to a statistical analysis for positively selected genes. We obtained 75 genes under positive selection and explored their potential for antibiotic resistance. We found that eight genes have functions relating to antibiotic resistance, such as biofilm formation, membrane permeability, and bacterial persistence. Finally, we correlated the presence/absence of non-synonymous mutations in positively selected sites of the genes with a function in resistance against 20 most prescribed antibiotics. We identified mutations associated with antibiotic resistance in two genes: the porin ompC and the bacterial persistence gene hipA. These mutations are located at the surface of the proteins and may hence have a direct effect on structure and function. For hipA, we hypothesize that the mutations influence its interaction with hipB and that they enhance the capacity for dormancy as a strategy to evade antibiotics. Overall, genomic data and positive selection analyses uncover novel insights into mechanisms driving antibiotic resistance.

Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities

Microbial communities might include distinct lineages of closely related organisms that complicate metagenomic assembly and prevent the generation of complete metagenome-assembled genomes (MAGs). Here we show that deep sequencing using long (HiFi) reads combined with Hi-C binning can address this challenge even for complex microbial communities. Using existing methods, we sequenced the sheep fecal metagenome and identified 428 MAGs with more than 90% completeness, including 44 MAGs in single circular contigs. To resolve closely related strains (lineages), we developed MAGPhase, which separates lineages of related organisms by discriminating variant haplotypes across hundreds of kilobases of genomic sequence. MAGPhase identified 220 lineage-resolved MAGs in our dataset. The ability to resolve closely related microbes in complex microbial communities improves the identification of biosynthetic gene clusters and the precision of assigning mobile genetic elements to host genomes. We identified 1,400 complete and 350 partial biosynthetic gene clusters, most of which are novel, as well as 424 (298) potential host-viral (host-plasmid) associations using Hi-C data.

Comparative Genomic Analysis of Stenotrophomonas maltophilia Strain W18 Reveals Its Adaptative Genomic Features for Degrading Polycyclic Aromatic Hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants that are ubiquitous in the environment. Numerous bacteria have evolved to have degrading genes or pathways to degrade PAHs. Stenotrophomonas maltophilia strain W18 was found to be able to degrade PAHs. Including 43 other complete genome sequences of S. maltophilia strains, we performed a comparative genomic analysis of 44 S. maltophilia strains by running OrthoFinder. A KEGG pathway enrichment analysis of environmental and clinical isolates of S. maltophilia revealed that environmental isolates tended to enhance gene functions such as "energy metabolism," "amino acid metabolism," "xenobiotic biodegradation and metabolism," and "folding, sorting, and degradation." The pangenome of the 44 S. maltophilia strains was open, while the core genome was estimated to reach a steady plateau. Based on gene annotations, we inferred that most of the degradation potential came from the core genome of S. maltophilia, while character genes and accessory genes also contributed to the degradation ability of S. maltophilia W18. The genes expression level of core genes, character genes and accessory genes were proved by RT-qPCR experiment, and accessory genes encoding alcohol dehydrogenase were upregulated most compared with genes with similar functions. We performed a credible comparative genomic analysis of S. maltophilia strains. S. maltophilia W18 was set as a model PAH-degrading bacterium of this species in this study, which would provide guidance for understanding and predicting the degradation mechanisms of other PAH-degrading S. maltophilia strains lacking complete genome data or waiting to be determined. IMPORTANCE This study provided the latest comparative genomic analysis on Stenotrophomonas maltophilia strains and focused on analyzing their genomic features that allow them to adapt to natural environments. In this study, we set S. maltophilia W18 as a typical PAH-degrading strain of this species. By discussing the genomic adaptative features of degrading PAH, we can predict genomic adaptative features of other S. maltophilia PAH-degrading strains since the core function of this species is stable. The gene functions of how S. maltophilia environmental isolates are enhanced for adaptation to various natural environments compared with clinical isolates have been revealed. Combined with a pangenome analysis and RT-qPCR results, we have proved that core genes, character genes, and accessory genes are all involved in PAH degradation. Accessory genes encoding alcohol dehydrogenase were upregulated most compared with core and character genes with similar functions, which suggests that PAH metabolization potential might be enhanced by horizontal gene transfer.

GENPPI: standalone software for creating protein interaction networks from genomes

BackGround

Bacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results.

Results

We developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 min on a conventional computer. Moreover, the interaction networks that our software creates reflect correct evolutionary relationships between species, which we confirmed with average nucleotide identity analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user’s choice regarding which set of genomes they are going to study.

Conclusions

GENPPI can help fill the gap concerning the considerable number of novel genomes assembled monthly and our ability to process interaction networks considering the noncore genes for all completed genome versions. With GENPPI, a user dictates how many and how evolutionarily correlated the genomes answer a scientific query.

Pangenomic Analysis of Dickeya dianthicola Strains Related to the Outbreak of Blackleg and Soft Rot of Potato in the United States

Dickeya dianthicola has caused an outbreak of blackleg and soft rot of potato in the eastern half of the United States since 2015. To investigate genetic diversity of the pathogen, a comparative analysis was conducted on genomes of D. dianthicola strains. Whole genomes of 16 strains from the United States outbreak were assembled and compared with 16 previously sequenced genomes of D. dianthicola isolated from potato or carnation. Among the 32 strains, eight distinct clades were distinguished based on phylogenomic analysis. The outbreak strains were grouped into three clades, with the majority of the strains in clade I. Clade I strains were unique and homogeneous, suggesting a recent incursion of this strain into potato production from alternative hosts or environmental sources. The pangenome of the 32 strains contained 6,693 genes, 3,377 of which were core genes. By screening primary protein subunits associated with virulence from all U.S. strains, we found that many virulence-related gene clusters, such as plant cell wall degrading enzyme genes, flagellar and chemotaxis related genes, two-component regulatory genes, and type I/II/III secretion system genes, were highly conserved but that type IV and type VI secretion system genes varied. The clade I strains encoded two clusters of type IV secretion systems, whereas the clade II and III strains encoded only one cluster. Clade I and II strains encoded one more VgrG/PAAR spike protein than did clade III. Thus, we predicted that the presence of additional virulence-related genes may have enabled the unique clade I strain to become predominant in the U.S. outbreak.

PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains

BACKGROUND

Discerning genes crucial to antimicrobial resistance (AMR) mechanisms is becoming more and more important to accurately and swiftly identify AMR pathogenic strains. Pangenome-wide association studies (e.g. Scoary) identified numerous putative AMR genes. However, only a tiny proportion of the putative resistance genes are annotated by AMR databases or Gene Ontology. In addition, many putative resistance genes are of unknown function (termed hypothetical proteins). An annotation tool is crucially needed in order to reveal the functional organization of the resistome and expand our knowledge of the AMR gene repertoire.

RESULTS

We developed an approach (PangenomeNet) for building co-functional networks from pan-genomes to infer functions for hypothetical genes. Using Escherichia coli as an example, we demonstrated that it is possible to build co-functional network from its pan-genome using co-inheritance, domain-sharing, and protein-protein-interaction information. The investigation of the network revealed that it fits the characteristics of biological networks and can be used for functional inferences. The subgraph consisting of putative meropenem resistance genes consists of clusters of stress response genes and resistance gene acquisition pathways. Resistome subgraphs also demonstrate drug-specific AMR genes such as beta-lactamase, as well as functional roles shared among multiple classes of drugs, mostly in the stress-related pathways.

CONCLUSIONS

By demonstrating the idea of pan-genome-based co-functional network on the E. coli species, we showed that the network can infer functional roles of the genes, including those without functional annotations, and provides holistic views on the putative antimicrobial resistomes. We hope that the pan-genome network idea can help formulate hypothesis for targeted experimental works.

Phylogenetic systematics of Butyrivibrio and Pseudobutyrivibrio genomes illustrate vast taxonomic diversity, open genomes and an abundance of carbohydrate-active enzyme family isoforms

Butyrivibrio and Pseudobutyrivibrio dominate in anaerobic gastrointestinal microbiomes, particularly the rumen, where they play a key role in harvesting dietary energy. Within these genera, five rumen species have been classified (Butyrivibrio fibrisolvens, Butyrivibrio hungatei, Butyrivibrio proteoclasticus, Pseudobutyrivibrio ruminis and Pseudobutyrivibrio xylanivorans) and more recently an additional Butyrivibrio sp. group was added. Given the recent increase in available genomes, we re-investigated the phylogenetic systematics and evolution of Butyrivibrio and Pseudobutyrivibrio. Across 71 genomes, we show using 16S rDNA and 40 gene marker phylogenetic trees that the current six species designations (P. ruminis, P. xylanivorans, B. fibrisolvens, Butyrivibrio sp., B. hungatei and B. proteclasticus) are found. However, pangenome analysis showed vast genomic variation and a high abundance of accessory genes (91.50–99.34 %), compared with core genes (0.66–8.50 %), within these six taxonomic groups, suggesting incorrectly assigned taxonomy. Subsequent pangenome accessory genomes under varying core gene cut-offs (%) and average nucleotide identity (ANI) analysis suggest the existence of 42 species within 32 genera. Pangenome analysis of those that still group within B. fibrisolvens, B. hungatei and P. ruminis, based on revised ANI phylogeny, also showed possession of very open genomes, illustrating the diversity that exists even within these groups. All strains of both Butyrivibrio and Pseudobutyrivibrio also shared a broad range of clusters of orthologous genes (COGs) (870), indicating recent evolution from a common ancestor. We also demonstrate that the carbohydrate-active enzymes (CAZymes) predominantly belong to glycosyl hydrolase (GH)2, 3, 5, 13 and 43, with numerous within family isoforms apparent, likely facilitating metabolic plasticity and resilience under dietary perturbations. This study provides a major advancement in our functional and evolutionary understanding of these important anaerobic bacteria.

Machine Learning Prediction of Resistance to Subinhibitory Antimicrobial Concentrations from Escherichia coli Genomes

Escherichia coli is an important cause of bacterial infections worldwide, with multidrug-resistant strains incurring substantial costs on human lives. Besides therapeutic concentrations of antimicrobials in health care settings, the presence of subinhibitory antimicrobial residues in the environment and in clinics selects for antimicrobial resistance (AMR), but the underlying genetic repertoire is less well understood. Here, we used machine learning to predict the population doubling time and cell growth yield of 1,407 genetically diverse E. coli strains expanding under exposure to three subinhibitory concentrations of six classes of antimicrobials from single-nucleotide genetic variants, accessory gene variation, and the presence of known AMR genes. We predicted cell growth yields in the held-out test data with an average correlation (Spearman's ρ) of 0.63 (0.36 to 0.81 across concentrations) and cell doubling times with an average correlation of 0.59 (0.32 to 0.92 across concentrations), with moderate increases in sample size unlikely to improve predictions further. This finding points to the remaining missing heritability of growth under antimicrobial exposure being explained by effects that are too rare or weak to be captured unless sample size is dramatically increased, or by effects other than those conferred by the presence of individual single-nucleotide polymorphisms (SNPs) and genes. Predictions based on whole-genome information were generally superior to those based only on known AMR genes and were accurate for AMR resistance at therapeutic concentrations. We pinpointed genes and SNPs determining the predicted growth and thereby recapitulated many known AMR determinants. Finally, we estimated the effect sizes of resistance genes across the entire collection of strains, disclosing the growth effects for known resistance genes in each individual strain. Our results underscore the potential of predictive modeling of growth patterns from genomic data under subinhibitory concentrations of antimicrobials, although the remaining missing heritability poses a challenge for achieving the accuracy and precision required for clinical use. IMPORTANCE Predicting bacterial growth from genome sequences is important for a rapid characterization of strains in clinical diagnostics and to disclose candidate novel targets for anti-infective drugs. Previous studies have dissected the relationship between bacterial growth and genotype in mutant libraries for laboratory strains, yet no study so far has examined the predictive power of genome sequence in natural strains. In this study, we used a high-throughput phenotypic assay to measure the growth of a systematic collection of natural Escherichia coli strains and then employed machine learning models to predict bacterial growth from genomic data under nontherapeutic subinhibitory concentrations of antimicrobials that are common in nonclinical settings. We found a moderate to strong correlation between predicted and actual values for the different collected data sets. Moreover, we observed that the known resistance genes are still effective at sublethal concentrations, pointing to clinical implications of these concentrations.

The microbiome extends host evolutionary potential

The microbiome shapes many host traits, yet the biology of microbiomes challenges traditional evolutionary models. Here, we illustrate how integrating the microbiome into quantitative genetics can help untangle complexities of host-microbiome evolution. We describe two general ways in which the microbiome may affect host evolutionary potential: by shifting the mean host phenotype and by changing the variance in host phenotype in the population. We synthesize the literature across diverse taxa and discuss how these scenarios could shape the host response to selection. We conclude by outlining key avenues of research to improve our understanding of the complex interplay between hosts and microbiomes.

Systematic Detection of Large-Scale Multigene Horizontal Transfer in Prokaryotes

Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the “scale” of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multigene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale data set of over 22,000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multigene transfer. Among other insights, we find that 1) the observed relative frequency of HMGT increases as divergence between genomes increases, 2) HMGTs often have conserved gene functions, and 3) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution.

The Thermosynechococcus Genus: Wide Environmental Distribution, but a Highly Conserved Genomic Core

Cyanobacteria thrive in diverse environments. However, questions remain about possible growth limitations in ancient environmental conditions. As a single genus, the Thermosynechococcus are cosmopolitan and live in chemically diverse habitats. To understand the genetic basis for this, we compared the protein coding component of Thermosynechococcus genomes. Supplementing the known genetic diversity of Thermosynechococcus, we report draft metagenome-assembled genomes of two Thermosynechococcus recovered from ferrous carbonate hot springs in Japan. We find that as a genus, Thermosynechococcus is genomically conserved, having a small pan-genome with few accessory genes per individual strain as well as few genes that are unique to the genus. Furthermore, by comparing orthologous protein groups, including an analysis of genes encoding proteins with an iron related function (uptake, storage or utilization), no clear differences in genetic content, or adaptive mechanisms could be detected between genus members, despite the range of environments they inhabit. Overall, our results highlight a seemingly innate ability for Thermosynechococcus to inhabit diverse habitats without having undergone substantial genomic adaptation to accommodate this. The finding of Thermosynechococcus in both hot and high iron environments without adaptation recognizable from the perspective of the proteome has implications for understanding the basis of thermophily within this clade, and also for understanding the possible genetic basis for high iron tolerance in cyanobacteria on early Earth. The conserved core genome may be indicative of an allopatric lifestyle-or reduced genetic complexity of hot spring habitats relative to other environments.

Development of a Multiplex PCR Assay for Genotyping the Fish Pathogen Piscirickettsia salmonis Through Comparative Genomics

Piscirickettsia salmonis is a bacterial pathogen that severely impact the aquaculture in several countries as Canada, Scotland, Ireland, Norway, and Chile. It provokes Piscirickettsiosis outbreaks in the marine phase of salmonid farming, resulting in economic losses. The monophyletic genogroup LF-89 and a divergent genogroup EM-90 are responsible for the most severe Piscirickettsiosis outbreaks in Chile. Therefore, the development of methods for quick genotyping of P. salmonis genogroups in field samples is vital for veterinary diagnoses and understanding the population structure of this pathogen. The present study reports the development of a multiplex PCR for genotyping LF-89 and EM-90 genogroups based on comparative genomics of 73 fully sequenced P. salmonis genomes. The results revealed 2,322 sequences shared between 35 LF-89 genomes, 2,280 sequences in the core-genome of 38 EM-90 genomes, and 331 and 534 accessory coding sequences each genogroup, respectively. A total of 1,801 clusters of coding sequences were shared among all tested genomes of P. salmonis (LF-89 and EM-90), with 253 and 291 unique sequences for LF-89 and EM-90 genogroups, respectively. The Multiplex-1 prototype was chosen for reliable genotyping because of differences in annealing temperatures and respective reaction efficiencies. This method also identified the pathogen in field samples infected with LF-89 or EM-90 strains, which is not possible with other methods currently available. Finally, the genome-based multiplex PCR protocol presented in this study is a rapid and affordable alternative to classical sequencing of PCR products and analyzing the length of restriction fragment polymorphisms.

Population genomics and antimicrobial resistance dynamics of Escherichia coli in wastewater and river environments

Aquatic environments are key niches for the emergence, evolution and dissemination of antimicrobial resistance. However, the population diversity and the genetic elements that drive the dynamics of resistant bacteria in different aquatic environments are still largely unknown. The aim of this study was to understand the population genomics and evolutionary events of Escherichia coli resistant to clinically important antibiotics including aminoglycosides, in anthropogenic and natural water ecosystems. Here we show that less different E. coli sequence types (STs) are identified in wastewater than in rivers, albeit more resistant to antibiotics, and with significantly more plasmids/cell (6.36 vs 3.72). However, the genomic diversity within E. coli STs in both aquatic environments is similar. Wastewater environments favor the selection of conserved chromosomal structures associated with diverse flexible plasmids, unraveling promiscuous interplasmidic resistance genes flux. On the contrary, the key driver for river E. coli adaptation is a mutable chromosome along with few plasmid types shared between diverse STs harboring a limited resistance gene content.

Genomic signatures of adaptation to natural settings in non-typhoidal Salmonella enterica Serovars Saintpaul, Thompson and Weltevreden

Salmonella enterica is a pathogenic bacterium responsible for intestinal illness and systemic diseases such as typhoid and paratyphoid fevers. Among clinical manifestation classification, non-typhoidal Salmonella is mainly known as foodborne pathogen associated with the consumption of fecal contaminated food and water. Even though Salmonella hosts include humans and warm-blooded animals, it has been found in non-host environments as river water where the bacteria use different strategies to fitness the environment persisting and establishment. Now with the availability of WGS and bioinformatics tools, we can explore bacterial genomes with higher resolution to increase our understanding of specific genetic signatures among environmental and clinical isolates, being the goal of this work. Pangenome construction allowed the detection of specific environmental and clinical gene clusters related to metabolism and secretion systems as the main signature respectively. Specifically, D-galactonate degradation pathway was observed mainly in environmental genomes while T3SS and flagellum genes were detected for all clinical but not for all environmental isolates. Gene duplication and pseudogenes accumulation were detected as the main adaptation strategy for environmental isolates; thus, isolation source may play an important role in genome plasticity, conferring a selective advantage to survive and persist for environmental Salmonella isolates. Intact prophage sequences with cargo genes were observable for both isolation sources playing an important role in virulence contribution.

Proteomics-Based Data Integration of Wheat Cultivars Facing Fusarium graminearum Strains Revealed a Core-Responsive Pattern Controlling Fusarium Head Blight

Fusarium head blight (FHB), mainly occurring upon Fusarium graminearum infection in a wide variety of small-grain cereals, is supposed to be controlled by a range of processes diverted by the fungal pathogen, the so-called susceptibility factors. As a mean to provide relevant information about the molecular events involved in FHB susceptibility in bread wheat, we studied an extensive proteome of more than 7,900 identified wheat proteins in three cultivars of contrasting susceptibilities during their interaction with three F. graminearum strains of different aggressiveness. No cultivar-specific proteins discriminated the three wheat genotypes, demonstrating the establishment of a core proteome regardless of unequivocal FHB susceptibility differences. Quantitative protein analysis revealed that most of the FHB-induced molecular adjustments were shared by wheat cultivars and occurred independently of the F. graminearum strain aggressiveness. Although subtle abundance changes evidenced genotype-dependent responses to FHB, cultivar distinction was found to be mainly due to basal abundance differences, especially regarding the chloroplast functions. Integrating these data with previous proteome mapping of the three F. graminearum strains facing the three same wheat cultivars, we demonstrated strong correlations between the wheat protein abundance changes and the adjustments of fungal proteins supposed to interfere with host molecular functions. Together, these results provide a resourceful dataset that expands our understanding of the specific molecular events taking place during the wheat-F. graminearum interaction.

Does diversity beget diversity in microbiomes?

Microbes are embedded in complex communities where they engage in a wide array of intra- and inter-specific interactions. The extent to which these interactions drive or impede microbiome diversity is not well understood. Historically, two contrasting hypotheses have been suggested to explain how species interactions could influence diversity. 'Ecological Controls' (EC) predicts a negative relationship, where the evolution or migration of novel types is constrained as niches become filled. In contrast, 'Diversity Begets Diversity' (DBD) predicts a positive relationship, with existing diversity promoting the accumulation of further diversity via niche construction and other interactions. Using high-throughput amplicon sequencing data from the Earth Microbiome Project, we provide evidence that DBD is strongest in low-diversity biomes, but weaker in more diverse biomes, consistent with biotic interactions initially favouring the accumulation of diversity (as predicted by DBD). However, as niches become increasingly filled, diversity hits a plateau (as predicted by EC).

Plasmids Related to the Symbiotic Nitrogen Fixation Are Not Only Cooperated Functionally but Also May Have Evolved over a Time Span in Family Rhizobiaceae

Rhizobia are soil bacteria capable of forming symbiotic nitrogen-fixing nodules associated with leguminous plants. In fast-growing legume-nodulating rhizobia, such as the species in the family Rhizobiaceae, the symbiotic plasmid is the main genetic basis for nitrogen-fixing symbiosis, and is susceptible to horizontal gene transfer. To further understand the symbioses evolution in Rhizobiaceae, we analyzed the pan-genome of this family based on 92 genomes of type/reference strains and reconstructed its phylogeny using a phylogenomics approach. Intriguingly, although the genetic expansion that occurred in chromosomal regions was the main reason for the high proportion of low-frequency flexible gene families in the pan-genome, gene gain events associated with accessory plasmids introduced more genes into the genomes of nitrogen-fixing species. For symbiotic plasmids, although horizontal gene transfer frequently occurred, transfer may be impeded by, such as, the host’s physical isolation and soil conditions, even among phylogenetically close species. During coevolution with leguminous hosts, the plasmid system, including accessory and symbiotic plasmids, may have evolved over a time span, and provided rhizobial species with the ability to adapt to various environmental conditions and helped them achieve nitrogen fixation. These findings provide new insights into the phylogeny of Rhizobiaceae and advance our understanding of the evolution of symbiotic nitrogen fixation.

Taxonomic classification method for metagenomics based on core protein families with Core-Kaiju

Characterizing species diversity and composition of bacteria hosted by biota is revolutionizing our understanding of the role of symbiotic interactions in ecosystems. Determining microbiomes diversity implies the assignment of individual reads to taxa by comparison to reference databases. Although computational methods aimed at identifying the microbe(s) taxa are available, it is well known that inferences using different methods can vary widely depending on various biases. In this study, we first apply and compare different bioinformatics methods based on 16S ribosomal RNA gene and shotgun sequencing to three mock communities of bacteria, of which the compositions are known. We show that none of these methods can infer both the true number of taxa and their abundances. We thus propose a novel approach, named Core-Kaiju, which combines the power of shotgun metagenomics data with a more focused marker gene classification method similar to 16S, but based on emergent statistics of core protein domain families. We thus test the proposed method on various mock communities and we show that Core-Kaiju reliably predicts both number of taxa and abundances. Finally, we apply our method on human gut samples, showing how Core-Kaiju may give more accurate ecological characterization and a fresh view on real microbiomes.

Unlocking the Genomic Taxonomy of the Prochlorococcus Collective

Prochlorococcus is the most abundant photosynthetic prokaryote on our planet. The extensive ecological literature on the Prochlorococcus collective (PC) is based on the assumption that it comprises one single genus comprising the species Prochlorococcus marinus, containing itself a collective of ecotypes. Ecologists adopt the distributed genome hypothesis of an open pan-genome to explain the observed genomic diversity and evolution patterns of the ecotypes within PC. Novel genomic data for the PC prompted us to revisit this group, applying the current methods used in genomic taxonomy. As a result, we were able to distinguish the five genera: Prochlorococcus, Eurycolium, Prolificoccus, Thaumococcus, and Riococcus. The novel genera have distinct genomic and ecological attributes.

Genome expansion in early eukaryotes drove the transition from lateral gene transfer to meiotic sex

Prokaryotes acquire genes from the environment via lateral gene transfer (LGT). Recombination of environmental DNA can prevent the accumulation of deleterious mutations, but LGT was abandoned by the first eukaryotes in favour of sexual reproduction. Here we develop a theoretical model of a haploid population undergoing LGT which includes two new parameters, genome size and recombination length, neglected by previous theoretical models. The greater complexity of eukaryotes is linked with larger genomes and we demonstrate that the benefit of LGT declines rapidly with genome size. The degeneration of larger genomes can only be resisted by increases in recombination length, to the same order as genome size - as occurs in meiosis. Our results can explain the strong selective pressure towards the evolution of sexual cell fusion and reciprocal recombination during early eukaryotic evolution - the origin of meiotic sex.

Pan-genomic analysis reveals that the evolution of Dietzia species depends on their living habitats

The bacterial genus Dietzia is widely distributed in various environments. The genomes of 26 diverse strains of Dietzia, including almost all the type strains, were analysed in this study. This analysis revealed a lipid metabolism gene richness, which could explain the ability of Dietzia to live in oil related environments. The pan-genome consists of 83,976 genes assigned into 10,327 gene families, 792 of which are shared by all the genomes of Dietzia. Mathematical extrapolation of the data suggests that the Dietzia pan-genome is open. Both gene duplication and gene loss contributed to the open pan-genome, while horizontal gene transfer was limited. Dietzia strains primarily gained their diverse metabolic capacity through more ancient gene duplications. Phylogenetic analysis of Dietzia isolated from aquatic and terrestrial environments showed two distinct clades from the same ancestor. The genome sizes of Dietzia strains from aquatic environments were significantly larger than those from terrestrial environments, which was mainly due to the occurrence of more gene loss events during the evolutionary progress of the strains from terrestrial environments. The evolutionary history of Dietzia was tightly coupled to environmental conditions, and iron concentrations should be one of the key factors shaping the genomes of the Dietzia lineages.

Pan-genomic open reading frames: A potential supplement of single nucleotide polymorphisms in estimation of heritability and genomic prediction

Pan-genomic open reading frames (ORFs) potentially carry protein-coding gene or coding variant information in a population. In this study, we suggest that pan-genomic ORFs are promising to be utilized in estimation of heritability and genomic prediction. A Saccharomyces cerevisiae dataset with whole-genome SNPs, pan-genomic ORFs, and the copy numbers of those ORFs is used to test the effectiveness of ORF data as a predictor in three prediction models for 35 traits. Our results show that the ORF-based heritability can capture more genetic effects than SNP-based heritability for all traits. Compared to SNP-based genomic prediction (GBLUP), pan-genomic ORF-based genomic prediction (OBLUP) is distinctly more accurate for all traits, and the predictive abilities on average are more than doubled across all traits. For four traits, the copy number of ORF-based prediction(CBLUP) is more accurate than OBLUP. When using different numbers of isolates in training sets in ORF-based prediction, the predictive abilities for all traits increased as more isolates are added in the training sets, suggesting that with very large training sets the prediction accuracy will be in the range of the square root of the heritability. We conclude that pan-genomic ORFs have the potential to be a supplement of single nucleotide polymorphisms in estimation of heritability and genomic prediction.

First Steps in the Analysis of Prokaryotic Pan-Genomes

Pan-genome is defined as the set of orthologous and unique genes of a specific group of organisms. The pan-genome is composed by the core genome, accessory genome, and species- or strain-specific genes. The pan-genome is considered open or closed based on the alpha value of the Heap law. In an open pan-genome, the number of gene families will continuously increase with the addition of new genomes to the analysis, while in a closed pan-genome, the number of gene families will not increase considerably. The first step of a pan-genome analysis is the homogenization of genome annotation. The same software should be used to annotate genomes, such as GeneMark or RAST. Subsequently, several software are used to calculate the pan-genome such as BPGA, GET_HOMOLOGUES, PGAP, among others. This review presents all these initial steps for those who want to perform a pan-genome analysis, explaining key concepts of the area. Furthermore, we present the pan-genomic analysis of 9 bacterial species. These are the species with the highest number of genomes deposited in GenBank. We also show the influence of the identity and coverage parameters on the prediction of orthologous and paralogous genes. Finally, we cite the perspectives of several research areas where pan-genome analysis can be used to answer important issues.

Comparative genomics and pangenome-oriented studies reveal high homogeneity of the agronomically relevant enterobacterial plant pathogen Dickeya solani

Background

Dickeya solani is an important plant pathogenic bacterium causing severe losses in European potato production. This species draws a lot of attention due to its remarkable virulence, great devastating potential and easier spread in contrast to other Dickeya spp. In view of a high need for extensive studies on economically important soft rot Pectobacteriaceae, we performed a comparative genomics analysis on D. solani strains to search for genetic foundations that would explain the differences in the observed virulence levels within the D. solani population.

Results

High quality assemblies of 8 de novo sequenced D. solani genomes have been obtained. Whole-sequence comparison, ANIb, ANIm, Tetra and pangenome-oriented analyses performed on these genomes and the sequences of 14 additional strains revealed an exceptionally high level of homogeneity among the studied genetic material of D. solani strains. With the use of 22 genomes, the pangenome of D. solani, comprising 84.7% core, 7.2% accessory and 8.1% unique genes, has been almost completely determined, suggesting the presence of a nearly closed pangenome structure. Attribution of the genes included in the D. solani pangenome fractions to functional COG categories showed that higher percentages of accessory and unique pangenome parts in contrast to the core section are encountered in phage/mobile elements- and transcription- associated groups with the genome of RNS 05.1.2A strain having the most significant impact. Also, the first D. solani large-scale genome-wide phylogeny computed on concatenated core gene alignments is herein reported.

Conclusions

The almost closed status of D. solani pangenome achieved in this work points to the fact that the unique gene pool of this species should no longer expand. Such a feature is characteristic of taxa whose representatives either occupy isolated ecological niches or lack efficient mechanisms for gene exchange and recombination, which seems rational concerning a strictly pathogenic species with clonal population structure. Finally, no obvious correlations between the geographical origin of D. solani strains and their phylogeny were found, which might reflect the specificity of the international seed potato market.

Population genomics of Vibrionaceae isolated from an endangered oasis reveals local adaptation after an environmental perturbation

Background

In bacteria, pan-genomes are the result of an evolutionary “tug of war” between selection and horizontal gene transfer (HGT). High rates of HGT increase the genetic pool and the effective population size (N_e), resulting in open pan-genomes. In contrast, selective pressures can lead to local adaptation by purging the variation introduced by HGT and mutation, resulting in closed pan-genomes and clonal lineages. In this study, we explored both hypotheses, elucidating the pan-genome of Vibrionaceae isolates after a perturbation event in the endangered oasis of Cuatro Ciénegas Basin (CCB), Mexico, and looking for signals of adaptation to the environments in their genomes.

Results

We obtained 42 genomes of Vibrionaceae distributed in six lineages, two of them did not showed any close reference strain in databases. Five of the lineages showed closed pan-genomes and were associated to either water or sediment environment; their high N_e estimates suggest that these lineages are not from a recent origin. The only clade with an open pan-genome was found in both environments and was formed by ten genetic groups with low N_e, suggesting a recent origin. The recombination and mutation estimators (r/m) ranged from 0.005 to 2.725, which are similar to oceanic Vibrionaceae estimations. However, we identified 367 gene families with signals of positive selection, most of them found in the core genome; suggesting that despite recombination, natural selection moves the Vibrionaceae CCB lineages to local adaptation, purging the genomes and keeping closed pan-genome patterns. Moreover, we identify 598 SNPs associated with an unstructured environment; some of the genes associated with these SNPs were related to sodium transport.

Conclusions

Different lines of evidence suggest that the sampled Vibrionaceae, are part of the rare biosphere usually living under famine conditions. Two of these lineages were reported for the first time. Most Vibrionaceae lineages of CCB are adapted to their micro-habitats rather than to the sampled environments. This pattern of adaptation is concordant with the association of closed pan-genomes and local adaptation.

The pan-genome of Saccharomyces cerevisiae

Understanding genotype-phenotype relationship is fundamental in biology. With the benefit from next-generation sequencing and high-throughput phenotyping methodologies, there have been generated much genome and phenome data for Saccharomyces cerevisiae. This makes it an excellent model system to understand the genotype-phenotype relationship. In this paper, we presented the reconstruction and application of the yeast pan-genome in resolving genotype-phenotype relationship by a machine learning-assisted approach.

Genome Comparison Identifies Different Bacillus Species in a Bast Fibre-Retting Bacterial Consortium and Provides Insights into Pectin Degrading Genes

Retting of bast fibres requires removal of pectin, hemicellulose and other non-cellulosic materials from plant stem tissues by a complex microbial community. A microbial retting consortium with high-efficiency pectinolytic bacterial strains is effective in reducing retting-time and enhancing fibre quality. We report comprehensive genomic analyses of three bacterial strains (PJRB 1, 2 and 3) of the consortium and resolve their taxonomic status, genomic features, variations, and pan-genome dynamics. The genome sizes of the strains are ~3.8 Mb with 3729 to 4002 protein-coding genes. Detailed annotations of the protein-coding genes revealed different carbohydrate-degrading CAZy classes viz. PL1, PL9, GH28, CE8, and CE12. Phylogeny and structural features of pectate lyase proteins of PJRB strains divulge their functional uniqueness and evolutionary convergence with closely related Bacillus strains. Genome-wide prediction of genomic variations revealed 12461 to 67381 SNPs, and notably many unique SNPs were localized within the important pectin metabolism genes. The variations in the pectate lyase genes possibly contribute to their specialized pectinolytic function during the retting process. These findings encompass a strong foundation for fundamental and evolutionary studies on this unique microbial degradation of decaying plant material with immense industrial significance. These have preponderant implications in plant biomass research and food industry, and also posit application in the reclamation of water pollution from plant materials.

Population structure and adaptation of a bacterial pathogen in California grapevines

Xylella fastidiosa subsp. fastidiosa causes Pierce's disease of grapevine (PD) and has been present in California for over a century. A singly introduced genotype spread across the state causing large outbreaks and damaging the grapevine industry. This study presents 122 X. fastidiosa subsp. fastidiosa genomes from symptomatic grapevines, and explores pathogen genetic diversity associated with PD in California. A total of 5218 single-nucleotide polymorphisms (SNPs) were found in the dataset. Strong population genetic structure was found; isolates split into five genetic clusters divided into two lineages. The core/soft-core genome constituted 41.2% of the total genome, emphasizing the high genetic variability of X. fastidiosa genomes. An ecological niche model was performed to estimate the environmental niche of the pathogen within California and to identify key climatic factors involved in dispersal. A landscape genomic approach was undertaken aiming to link local adaptation to climatic factors. A total of 18 non-synonymous polymorphisms found to be under selective pressures were correlated with at least one environmental variable highlighting the role of temperature, precipitation and elevation on X. fastidiosa adaptation to grapevines in California. Finally, the contribution to virulence of three of the genes under positive selective pressure and of one recombinant gene was studied by reverse genetics.

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

The use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. These methods usually lack multivariate statistical models to infer the partitions and the optimal number of classes and don't account for genome organization. We introduce a graph structure to model pangenomes in which nodes represent gene families and edges represent genomic neighborhood. Our method, named PPanGGOLiN, partitions nodes using an Expectation-Maximization algorithm based on multivariate Bernoulli Mixture Model coupled with a Markov Random Field. This approach takes into account the topology of the graph and the presence/absence of genes in pangenomes to classify gene families into persistent, cloud, and one or several shell partitions. By analyzing the partitioned pangenome graphs of isolate genomes from 439 species and metagenome-assembled genomes from 78 species, we demonstrate that our method is effective in estimating the persistent genome. Interestingly, it shows that the shell genome is a key element to understand genome dynamics, presumably because it reflects how genes present at intermediate frequencies drive adaptation of species, and its proportion in genomes is independent of genome size. The graph-based approach proposed by PPanGGOLiN is useful to depict the overall genomic diversity of thousands of strains in a compact structure and provides an effective basis for very large scale comparative genomics. The software is freely available at https://github.com/labgem/PPanGGOLiN.

Comparative Genome Analysis of Psychrobacillus Strain PB01, Isolated from an Iceberg

A novel psychrotolerant Psychrobacillus strain PB01, isolated from an Antarctic iceberg, was comparatively analyzed with five related strains. The complete genome of strain PB01 consists of a single circular chromosome (4.3 Mb) and a plasmid (19 Kb). As potential low-temperature adaptation strategies, strain PB01 has four genes encoding cold-shock proteins, two genes encoding DEAD-box RNA helicases, and eight genes encoding transporters for glycine betaine, which can serve as a cryoprotectant, on the genome. The pan-genome structure of the six Psychrobacillus strains suggests that strain PB01 might have evolved to adapt to extreme environments by changing its genome content to gain higher capacity for DNA repair, translation, and membrane transport. Notably, strain PB01 possesses a complete TCA cycle consisting of eight enzymes as well as three additional Helicobacter pylori-type enzymes: ferredoxin-dependent 2-oxoglutarate synthase, succinyl-CoA/acetoacetyl-CoA transferase, and malate/quinone oxidoreductase. The co-existence of the genes for TCA cycle enzymes has also been identified in the other five Psychrobacillus strains.

Comparative genomics of Lactobacillus fermentum suggests a free-living lifestyle of this lactic acid bacterial species

Lactobacillus fermentum is a lactic acid bacterium frequently isolated from mammal tissues, milk, and plant material fermentations, such as sourdough. A comparative genomics analysis of 28 L. fermentum strains enabled the investigation of the core and accessory genes of this species. The core protein phylogenomic tree of the strains examined, consisting of five clades, did not exhibit clear clustering of strains based on isolation source, suggesting a free-living lifestyle. Based on the presence/absence of orthogroups, the largest clade, containing most of the human-related strains, was separated from the rest. The extended core genome included genes necessary for the heterolactic fermentation. Many traits were found to be strain-dependent, for instance utilisation of xylose and arabinose. Compared to other strains, the genome of L. fermentum IMDO 130101, a candidate starter culture strain capable of dominating sourdough fermentations, contained unique genes related to the metabolism of starch degradation products, which could be advantageous for growth in sourdough matrices. This study explained the traits that were previously demonstrated for L. fermentum IMDO 130101 at the genetic level and provided future avenues of research regarding L. fermentum strains isolated from sourdough.