SARS-CoV-2 BW lineage, a fast-growing Omicron variant from southeast Mexico bearing relevant escape mutations.

PURPOSE: The swift expansion of the BW.1 SARS-CoV-2 variant coincided with a rapid increase of COVID-19 cases occurring in Southeast Mexico in October, 2022, which marked the start of Mexico's sixth epidemiological wave. In Yucatan, up to 92% (58 of 73) of weekly sequenced genomes between epidemiological week 42 and 47 were identified as either BW.1 or its descendant, BW.1.1 in the region, during the last trimester of 2022. In the current study, a comprehensive genomic comparison was carried out to characterize the evolutionary history of the BW lineage, identifying its origins and its most important mutations. METHODS: An alignment of all the genomes of the BW lineage and its parental BA.5.6.2 variant was carried out to identify their mutations. A phylogenetic and ancestral sequence reconstruction analysis with geographical inference, as well as a longitudinal analysis of point mutations, were performed to trace back their origin and contrast them with key RBD mutations in variant BQ.1, one of the fastest-growing lineages to date. RESULTS: Our ancestral reconstruction analysis portrayed Mexico as the most probable origin of the BW.1 and BW.1.1 variants. Two synonymous substitutions, T7666C and C14599T, support their Mexican origin, whereas other two mutations are specific to BW.1: S:N460K and ORF1a:V627I. Two additional substitutions and a deletion are found in its descending subvariant, BW.1.1. Mutations found in the receptor binding domain, S:K444T, S:L452R, S:N460K, and S:F486V in BW.1 have been reported to be relevant for immune escape and are also key mutations in the BQ.1 lineage. CONCLUSIONS: BW.1 appears to have arisen in the Yucatan Peninsula in Southeast Mexico sometime around July 2022 during the fifth COVID-19 wave. Its rapid growth may be in part explained by the relevant escape mutations also found in BQ.1.

Metagenomic analysis reveals differences in the co-occurrence and abundance of viral species in SARS-CoV-2 patients with different severity of disease.

BACKGROUND: SARS-CoV-2 infections have a wide spectrum of clinical manifestations whose causes are not completely understood. Some human conditions predispose to severe outcome, like old age or the presence of comorbidities, but many other facets, including coinfections with other viruses, remain poorly characterized. METHODS: In this study, the eukaryotic fraction of the respiratory virome of 120 COVID-19 patients was characterized through whole metagenomic sequencing. RESULTS: Genetic material from respiratory viruses was detected in 25% of all samples, whereas human viruses other than SARS-CoV-2 were found in 80% of them. Samples from hospitalized and deceased patients presented a higher prevalence of different viruses when compared to ambulatory individuals. Small circular DNA viruses from the Anneloviridae (Torque teno midi virus 8, TTV-like mini virus 19 and 26) and Cycloviridae families (Human associated cyclovirus 10), Human betaherpesvirus 6, were found to be significantly more abundant in samples from deceased and hospitalized patients compared to samples from ambulatory individuals. Similarly, Rotavirus A, Measles morbillivirus and Alphapapilomavirus 10 were significantly more prevalent in deceased patients compared to hospitalized and ambulatory individuals. CONCLUSIONS: Results show the suitability of using metagenomics to characterize a broader peripheric virological landscape of the eukaryotic virome in SARS-CoV-2 infected patients with distinct disease outcomes. Identified prevalent viruses in hospitalized and deceased patients may prove important for the targeted exploration of coinfections that may impact prognosis.

Metatranscriptomic analysis to define the Secrebiome, and 16S rRNA profiling of the gut microbiome in obesity and metabolic syndrome of Mexican children.

BACKGROUND: In the last decade, increasing evidence has shown that changes in human gut microbiota are associated with diseases, such as obesity. The excreted/secreted proteins (secretome) of the gut microbiota affect the microbial composition, altering its colonization and persistence. Furthermore, it influences microbiota-host interactions by triggering inflammatory reactions and modulating the host's immune response. The metatranscriptome is essential to elucidate which genes are expressed under diseases. In this regard, little is known about the expressed secretome in the microbiome. Here, we use a metatranscriptomic approach to delineate the secretome of the gut microbiome of Mexican children with normal weight (NW) obesity (O) and obesity with metabolic syndrome (OMS). Additionally, we performed the 16S rRNA profiling of the gut microbiota. RESULTS: Out of the 115,712 metatranscriptome genes that codified for proteins, 30,024 (26%) were predicted to be secreted, constituting the Secrebiome of the gut microbiome. The 16S profiling confirmed an increased abundance in Firmicutes and decreased in Bacteroidetes in the obesity groups, and a significantly higher richness and diversity than the normal weight group. We found novel biomarkers for obesity with metabolic syndrome such as increased Coriobacteraceae, Collinsela, and Collinsella aerofaciens; Erysipelotrichaceae, Catenibacterium and Catenibacterium sp., and decreased Parabacteroides distasonis, which correlated with clinical and anthropometric parameters associated to obesity and metabolic syndrome. Related to the Secrebiome, 16 genes, homologous to F. prausniitzi, were overexpressed for the obese and 15 genes homologous to Bacteroides, were overexpressed in the obesity with metabolic syndrome. Furthermore, a significant enrichment of CAZy enzymes was found in the Secrebiome. Additionally, significant differences in the antigenic density of the Secrebiome were found between normal weight and obesity groups. CONCLUSIONS: These findings show, for the first time, the role of the Secrebiome in the functional human-microbiota interaction. Our results highlight the importance of metatranscriptomics to provide novel information about the gut microbiome's functions that could help us understand the impact of the Secrebiome on the homeostasis of its human host. Furthermore, the metatranscriptome and 16S profiling confirmed the importance of treating obesity and obesity with metabolic syndrome as separate conditions to better understand the interplay between microbiome and disease.

Comparison of different assembly and annotation tools on analysis of simulated viral metagenomic communities in the gut.

BACKGROUND: The main limitations in the analysis of viral metagenomes are perhaps the high genetic variability and the lack of information in extant databases. To address these issues, several bioinformatic tools have been specifically designed or adapted for metagenomics by improving read assembly and creating more sensitive methods for homology detection. This study compares the performance of different available assemblers and taxonomic annotation software using simulated viral-metagenomic data. RESULTS: We simulated two 454 viral metagenomes using genomes from NCBI's RefSeq database based on the list of actual viruses found in previously published metagenomes. Three different assembly strategies, spanning six assemblers, were tested for performance: overlap-layout-consensus algorithms Newbler, Celera and Minimo; de Bruijn graphs algorithms Velvet and MetaVelvet; and read probabilistic model Genovo. The performance of the assemblies was measured by the length of resulting contigs (using N50), the percentage of reads assembled and the overall accuracy when comparing against corresponding reference genomes. Additionally, the number of chimeras per contig and the lowest common ancestor were estimated in order to assess the effect of assembling on taxonomic and functional annotation. The functional classification of the reads was evaluated by counting the reads that correctly matched the functional data previously reported for the original genomes and calculating the number of over-represented functional categories in chimeric contigs. The sensitivity and specificity of tBLASTx, PhymmBL and the k-mer frequencies were measured by accurate predictions when comparing simulated reads against the NCBI Virus genomes RefSeq database. CONCLUSIONS: Assembling improves functional annotation by increasing accurate assignations and decreasing ambiguous hits between viruses and bacteria. However, the success is limited by the chimeric contigs occurring at all taxonomic levels. The assembler and its parameters should be selected based on the focus of each study. Minimo's non-chimeric contigs and Genovo's long contigs excelled in taxonomy assignation and functional annotation, respectively.tBLASTx stood out as the best approach for taxonomic annotation for virus identification. PhymmBL proved useful in datasets in which no related sequences are present as it uses genomic features that may help identify distant taxa. The k-frequencies underperformed in all viral datasets.

Exploration of low-frequency allelic variants of SARS-CoV-2 genomes reveals coinfections in Mexico occurred during periods of VOCs turnover.

A total of 14 973 alleles in 29 661 sequenced samples collected between March 2021 and January 2023 by the Mexican Consortium for Genomic Surveillance (CoViGen-Mex) and collaborators were used to construct a thorough map of mutations of the Mexican SARS-CoV-2 genomic landscape containing Intra-Patient Minor Allelic Variants (IPMAVs), which are low-frequency alleles not ordinarily present in a genomic consensus sequence. This additional information proved critical in identifying putative coinfecting variants included alongside the most common variants, B.1.1.222, B.1.1.519, and variants of concern (VOCs) Alpha, Gamma, Delta, and Omicron. A total of 379 coinfection events were recorded in the dataset (a rate of 1.28 %), resulting in the first such catalogue in Mexico. The most common putative coinfections occurred during the spread of Delta or after the introduction of Omicron BA.2 and its descendants. Coinfections occurred constantly during periods of variant turnover when more than one variant shared the same niche and high infection rate was observed, which was dependent on the local variants and time. Coinfections might occur at a higher frequency than customarily reported, but they are often ignored as only the consensus sequence is reported for lineage identification.

SARS-CoV-2 Omicron variants BA.4 and BA.5 dominated the fifth COVID-19 epidemiological wave in Mexico.

In Mexico, the BA.4 and BA.5 Omicron variants dominated the fifth epidemic wave (summer 2022), superseding BA.2, which had circulated during the inter-wave period. The present study uses genome sequencing and statistical and phylogenetic analyses to examine these variants' abundance, distribution, and genetic diversity in Mexico from April to August 2022. Over 35 % of the sequenced genomes in this period corresponded to the BA.2 variant, 8 % to the BA.4 and 56 % to the BA.5 variant. Multiple subvariants were identified, but the most abundant, BA.2.9, BA.2.12.1, BA.5.1, BA.5.2, BA.5.2.1 and BA.4.1, circulated across the entire country, not forming geographical clusters. Contrastingly, other subvariants exhibited a geographically restricted distribution, most notably in the Southeast region, which showed a distinct subvariant dynamic. This study supports previous results showing that this region may be a significant entry point and contributed to introducing and evolving novel variants in Mexico. Furthermore, a differential distribution was observed for certain subvariants among specific States through time, which may have contributed to the overall increased diversity observed during this wave compared to the previous ones. This study highlights the importance of sustaining genomic surveillance to identify novel variants that may impact public health.

Omicron-BA.1 Dispersion Rates in Mexico Varied According to the Regional Epidemic Patterns and the Diversity of Local Delta Subvariants.

PURPOSE: The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In this work, a characterization of the spread of this variant in Mexico is presented. METHODS: The time to fixation of BA.1, the diversity of Delta sublineages, the population density, and the level of virus circulation during the inter-wave interval were determined to analyze differences in BA.1 spread. RESULTS: BA.1 began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in Mexico. Unlike previous variants, BA.1 did not exhibit a geographically distinct circulation pattern. However, a regional difference in the speed of the replacement of the Delta variant was observed. CONCLUSIONS: Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics, in addition to population density. Nonetheless, if there is a significant difference in the fitness of the variants, or if the time allowed for the competition is sufficiently long, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico.

The New SARS-CoV-2 Variants and Their Epidemiological Impact in Mexico.

The COVID-19 disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus started its deadly journey into a global pandemic in Wuhan, China, in December 2019, where it was first isolated. Subsequently, multiple variants of the virus have been identified worldwide. In this review, we discuss the overall landscape of the pandemic in Mexico, including its most prevalent variants, their surveillance at a genomic level, and how they impacted the epidemiology of the disease. We also evaluate the heterologous vaccination in Mexico and how it may have influenced group immunity and helped mitigate the pandemic. Finally, we present an integrated view that could help us to understand the pandemic and serve as an example of the situation in Latin America.

Two-year follow-up of the COVID-19 pandemic in Mexico.

Background: After the initial outbreak in China (December 2019), the World Health Organization declared COVID-19 a pandemic on March 11th, 2020. This paper aims to describe the first 2 years of the pandemic in Mexico. Design and methods: This is a population-based longitudinal study. We analyzed data from the national COVID-19 registry to describe the evolution of the pandemic in terms of the number of confirmed cases, hospitalizations, deaths and reported symptoms in relation to health policies and circulating variants. We also carried out logistic regression to investigate the major risk factors for disease severity. Results: From March 2020 to March 2022, the coronavirus disease 2019 (COVID-19) pandemic in Mexico underwent four epidemic waves. Out of 5,702,143 confirmed cases, 680,063 were hospitalized (11.9%), and 324,436 (5.7%) died. Even if there was no difference in susceptibility by gender, males had a higher risk of death (CFP: 7.3 vs. 4.2%) and hospital admission risk (HP: 14.4 vs. 9.5%). Severity increased with age. With respect to younger ages (0-17 years), the 60+ years or older group reached adjusted odds ratios of 9.63 in the case of admission and 53.05 (95% CI: 27.94-118.62) in the case of death. The presence of any comorbidity more than doubled the odds ratio, with hypertension-diabetes as the riskiest combination. While the wave peaks increased over time, the odds ratios for developing severe disease (waves 2, 3, and 4 to wave 1) decreased to 0.15 (95% CI: 0.12-0.18) in the fourth wave. Conclusion: The health policy promoted by the Mexican government decreased hospitalizations and deaths, particularly among older adults with the highest risk of admission and death. Comorbidities augment the risk of developing severe illness, which is shown to rise by double in the Mexican population, particularly for those reported with hypertension-diabetes. Factors such as the decrease in the severity of the SARS-CoV2 variants, changes in symptomatology, and advances in the management of patients, vaccination, and treatments influenced the decrease in mortality and hospitalizations.

Dominance of Three Sublineages of the SARS-CoV-2 Delta Variant in Mexico.

In this study, we analyzed the sequences of SARS-CoV-2 isolates of the Delta variant in Mexico, which has completely replaced other previously circulating variants in the country due to its transmission advantage. Among all the Delta sublineages that were detected, 81.5 % were classified as AY.20, AY.26, and AY.100. According to publicly available data, these only reached a world prevalence of less than 1%, suggesting a possible Mexican origin. The signature mutations of these sublineages are described herein, and phylogenetic analyses and haplotype networks are used to track their spread across the country. Other frequently detected sublineages include AY.3, AY.62, AY.103, and AY.113. Over time, the main sublineages showed different geographical distributions, with AY.20 predominant in Central Mexico, AY.26 in the North, and AY.100 in the Northwest and South/Southeast. This work describes the circulation, from May to November 2021, of the primary sublineages of the Delta variant associated with the third wave of the COVID-19 pandemic in Mexico and highlights the importance of SARS-CoV-2 genomic surveillance for the timely identification of emerging variants that may impact public health.

The Alpha Variant (B.1.1.7) of SARS-CoV-2 Failed to Become Dominant in Mexico.

During the coronavirus disease 2019 (COVID-19) pandemic, the emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in the United Kingdom in September 2020, was well documented in different areas of the world and became a global public health concern because of its increased transmissibility. The B.1.1.7 lineage was first detected in Mexico during December 2020, showing a slow progressive increase in its circulation frequency, which reached its maximum in May 2021 but never became predominant. In this work, we analyzed the patterns of diversity and distribution of this lineage in Mexico using phylogenetic and haplotype network analyses. Despite the reported increase in transmissibility of the B.1.1.7 lineage, in most Mexican states, it did not displace cocirculating lineages, such as B.1.1.519, which dominated the country from February to May 2021. Our results show that the states with the highest prevalence of B.1.1.7 were those at the Mexico-U.S. border. An apparent pattern of dispersion of this lineage from the northern states of Mexico toward the center or the southeast was observed in the largest transmission chains, indicating possible independent introduction events from the United States. However, other entry points cannot be excluded, as shown by multiple introduction events. Local transmission led to a few successful haplotypes with a localized distribution and specific mutations indicating sustained community transmission. IMPORTANCE The emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world were due to its increased transmissibility. However, it did not displace cocirculating lineages in most of Mexico, particularly B.1.1.519, which dominated the country from February to May 2021. In this work, we analyzed the distribution of B.1.1.7 in Mexico using phylogenetic and haplotype network analyses. Our results show that the states with the highest prevalence of B.1.1.7 (around 30%) were those at the Mexico-U.S. border, which also exhibited the highest lineage diversity, indicating possible introduction events from the United States. Also, several haplotypes were identified with a localized distribution and specific mutations, indicating that sustained community transmission occurred in the country.

OTUs and ASVs Produce Comparable Taxonomic and Diversity from Shrimp Microbiota 16S Profiles Using Tailored Abundance Filters.

The interplay between shrimp immune system, its environment, and microbiota contributes to the organism's homeostasis and optimal production. The metagenomic composition is typically studied using 16S rDNA profiling by clustering amplicon sequences into operational taxonomic units (OTUs) and, more recently, amplicon sequence variants (ASVs). Establish the compatibility of the taxonomy, α, and ß diversity described by both methods is necessary to compare past and future shrimp microbiota studies. Here, we used identical sequences to survey the V3 16S hypervariable-region using 97% and 99% OTUs and ASVs to assess the hepatopancreas and intestine microbiota of L. vannamei from two ponds under standardized rearing conditions. We found that applying filters to retain clusters >0.1% of the total abundance per sample enabled a consistent taxonomy comparison while preserving >94% of the total reads. The three sets turned comparable at the family level, whereas the 97% identity OTU set produced divergent genus and species profiles. Interestingly, the detection of organ and pond variations was robust to the clustering method's choice, producing comparable α and ß-diversity profiles. For comparisons on shrimp microbiota between past and future studies, we strongly recommend that ASVs be compared at the family level to 97% identity OTUs or use 99% identity OTUs, both using tailored frequency filters.

Gut dsDNA virome shows diversity and richness alterations associated with childhood obesity and metabolic syndrome.

Changes in the human gut microbiome are associated with obesity and metabolic syndrome, but the role of the gut virome in both diseases remains largely unknown. We characterized the gut dsDNA virome of 28 school-aged children with healthy normal-weight (NW, n = 10), obesity (O, n = 10), and obesity with metabolic syndrome (OMS, n = 8), using metagenomic sequencing of virus-like particles (VLPs) from fecal samples. The virome classification confirmed the bacteriophages' dominance, mainly composed of Caudovirales. Notably, phage richness and diversity of individuals with O and OMS tended to increase, while the VLP abundance remained the same among all groups. Of the 4,611 phage contigs composing the phageome, 48 contigs were highly prevalent in ≥80% of individuals, suggesting high inter-individual phage diversity. The abundance of several contigs correlated with gut bacterial taxa; and with anthropometric and biochemical parameters altered in O and OMS. To our knowledge, this gut phageome represents one of the largest datasets and suggests disease-specific phage alterations.

Genetic characterization of indigenous peoples from Oaxaca, Mexico, and its relation to linguistic and geographic isolation.

We used 15 short tandem repeat (STR) loci (D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, VWA, TPOX, D18S51, D5S818, and FGA) to genetically characterize 361 individuals from 11 indigenous populations (Amuzgo, Chinanteco, Chontal, Huave, Mazateco, Mixe, Mixteco, Triqui, Zapoteco del Istmo, Zapoteco del Valle, and Zoque) from Oaxaca, Mexico. We also used previously published data from other Mexican peoples (Maya, Chol, Tepehua, Otomí, and Mestizos from northern and central Mexico) to delineate genetic relations, for a total of 541 individuals. Average heterozygosity (H) was lower in most populations from Oaxaca (range 0.687 in Zoque to 0.756 in Chontal) than values observed in Mestizo populations from Mexico (0.758 and 0.793 in central and northern Mestizo, respectively) but higher than values observed in other Amerindian populations from South America; the same relation was true for the number of alleles (n(a) ). We tested (using the software Structure) whether major geographic or linguistic barriers to gene flow existed among the populations of Oaxaca and found that the populations appeared to constitute one or two genetic groups, suggesting that neither geographic location nor linguistics had an effect on the genetic structure of these culturally and linguistically highly diverse indigenous peoples. Moreover, we found a low but statistically significant between-population differentiation. In addition, the genetic structure of Oaxacan populations did not fit an isolation-by-distance model. Finally, using AMOVA and a Bayesian clustering approach, we did not detect significant geographic or linguistic barriers to gene flow within Oaxaca. These results suggest that the indigenous communities of Oaxaca, although culturally isolated, can be genetically defined as a large, nearly panmictic population in which migration could be a more important population mechanism than genetic drift. Finally, compared with outgroups in Mexico (both indigenous peoples and Mestizos), three groups were apparent. Among them, only the Otomí population from Hidalgo has a different culture and language.

Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota.

The shrimp has become the most valuable traded marine product in the world, and its microbiota plays an essential role in its development and overall health status. Massive high-throughput sequencing techniques using several hypervariable regions of the 16S rRNA gene are broadly applied in shrimp microbiota studies. However, it is essential to consider that the use of different hypervariable regions can influence the obtained data and the interpretation of the results. The present study compares the shrimp microbiota structure and composition obtained by three types of amplicons: one spanning both the V3 and V4 hypervariable regions (V3V4), one for the V3 region only (V3), and one for the V4 region only (V4) using the same experimental and bioinformatics protocols. Twenty-four samples from hepatopancreas and intestine were sequenced and evaluated using the GreenGenes and silva reference databases for clustering and taxonomic classification. In general, the V3V4 regions resulted in higher richness and diversity, followed by V3 and V4. All three regions establish an apparent clustering effect that discriminates between the two analyzed organs and describe a higher richness for the intestine and a higher diversity for the hepatopancreas samples. Proteobacteria was the most abundant phyla overall, and Cyanobacteria was more common in the intestine, whereas Firmicutes and Actinobacteria were more prevalent in hepatopancreas samples. Also, the genus Vibrio was significantly abundant in the intestine, as well as Acinetobacter and Pseudomonas in the hepatopancreas suggesting these taxa as markers for their respective organs independently of the sequenced region. The use of a single hypervariable region such as V3 may be a low-cost alternative that enables an adequate description of the shrimp microbiota, allowing for the development of strategies to continually monitor the microbial communities and detect changes that could indicate susceptibility to pathogens under real aquaculture conditions while the use of the full V3V4 regions can contribute to a more in-depth characterization of the microbial composition.

Beyond cells - The virome in the human holobiont.

Viromics, or viral metagenomics, is a relatively new and burgeoning field of research that studies the complete collection of viruses forming part of the microbiota in any given niche. It has strong foundations rooted in over a century of discoveries in the field of virology and recent advances in molecular biology and sequencing technologies. Historically, most studies have deconstructed the concept of viruses into a simplified perception of viral agents as mere pathogens, which demerits the scope of large-scale viromic analyses. Viruses are, in fact, much more than regular parasites. They are by far the most dynamic and abundant entity and the greatest killers on the planet, as well as the most effective geo-transforming genetic engineers and resource recyclers, acting on all life strata in any habitat. Yet, most of this uncanny viral world remains vastly unexplored to date, greatly hindered by the bewildering complexity inherent to such studies and the methodological and conceptual limitations. Viromic studies are just starting to address some of these issues but they still lag behind microbial metagenomics. In recent years, however, higher-throughput analysis and resequencing have rekindled interest in a field that is just starting to show its true potential. In this review, we take a look at the scientific and technological developments that led to the advent of viral and bacterial metagenomics with a particular, but not exclusive, focus on human viromics from an ecological perspective. We also address some of the most relevant challenges that current viral studies face and ponder on the future directions of the field.

Profiling of Protein Degraders in Cultures of Human Gut Microbiota.

Unabsorbed proteins reach the colon and are fermented by the microbiota, yielding a variety of harmful metabolites. In the present study, a 16S rRNA gene survey identified the bacterial taxa flourishing in 11 batch fermentations with proteins and peptones as the sole fermentable substrates, inoculated with the feces of six healthy adults. Organic acids, ammonia, and indole resulting from protein breakdown and fermentation accumulated in all of the cultures. Analysis of differential abundances among time-points identified Enterobacteriaceae, Burkholderiaceae, and Desulfovibrionaceae (including Esherichia-Shigella, Sutterella, Parasutterella, and Bilophila) among the bacteria that especially in the cultures with low inoculation load. Lachnospiraceae and Ruminococcaceae also encompassed many taxa that significantly expanded, mainly in cultures inoculated with high inoculation load, and showed the strongest correlation with the production of ammonium, indole, and p-cresol. Anaerotruncus, Dorea, Oscillibacter, Eubacterium oxidoreducens, Lachnoclostridium, Paeniclostridium, and Rombutsia were among them. Other Firmicutes (e.g., Roseburia, Ruminococcus, Lachnospira, Dialister, Erysipelotrichaceae, and Streptococcaceae) and many Bacteroidetes (e.g., Barnesiellaceae, Prevotellaceae, and Rickenelliaceae) decreased. Sequences attributed to Bacteroides, unresolved at the level of species, presented opposite contributions, resulting in no significant changes in the genus. This study sheds light on the multitude of bacterial taxa putatively participating in protein catabolism in the colon. Protein fermentation was confirmed as unfavorable to health, due to both the production of toxic metabolites and the blooming of opportunistic pathogens and pro-inflammatory bacteria.

Construction of a Comprehensive Database from the Existing Viral Sequences Available from the International Nucleotide Sequence Database Collaboration.

The progress in viromics research has led to the accumulation of a large number of sequences from different types of viruses obtained from different sources. Most databases are specific to different of species or types of viruses. However, raw sequences, as deposited in the reliable online collections, provide a valuable asset in the exploration of genomic and metagenomics datasets.The International Nucleotide Sequence Database Collaboration (INSDC) is the largest coordinated effort for compiling, sharing, and maintaining the most comprehensive collections of nucleic acids deposited throughout the most important public databases. The compendium includes different types of data such as complete genomes, genes, expressed sequence tags, and data generated by whole genome shotgun analyses spanning all domains of life, as well as the most complete collection of viral sequences available online.This chapter presents simplified computational methods for the automation of viral nucleotide sequence retrieval from online repositories of the INSDC databases, including all available sequences, except synthetic ones. The subsequent steps can be used for obtaining the taxonomy (including ranks: virus type, baltimore classification, order, family, subfamily, genus and species), and split the database into species subsets to dereplicate the sequences for other downstream applications. Only basic computational knowledge is required.

Fragmentation and Coverage Variation in Viral Metagenome Assemblies, and Their Effect in Diversity Calculations.

Metagenomic libraries consist of DNA fragments from diverse species, with varying genome size and abundance. High-throughput sequencing platforms produce large volumes of reads from these libraries, which may be assembled into contigs, ideally resembling the original larger genomic sequences. The uneven species distribution, along with the stochasticity in sample processing and sequencing bias, impacts the success of accurate sequence assembly. Several assemblers enable the processing of viral metagenomic data de novo, generally using overlap layout consensus or de Bruijn graph approaches for contig assembly. The success of viral genomic reconstruction in these datasets is limited by the degree of fragmentation of each genome in the sample, which is dependent on the sequencing effort and the genome length. Depending on ecological, biological, or procedural biases, some fragments have a higher prevalence, or coverage, in the assembly. However, assemblers must face challenges, such as the formation of chimerical structures and intra-species variability. Diversity calculation relies on the classification of the sequences that comprise a metagenomic dataset. Whenever the corresponding genomic and taxonomic information is available, contigs matching the same species can be classified accordingly and the coverage of its genome can be calculated for that species. This may be used to compare populations by estimating abundance and assessing species distribution from this data. Nevertheless, the coverage does not take into account the degree of fragmentation, or else genome completeness, and is not necessarily representative of actual species distribution in the samples. Furthermore, undetermined sequences are abundant in viral metagenomic datasets, resulting in several independent contigs that cannot be assigned by homology or genomic information. These may only be classified as different operational taxonomic units (OTUs), sometimes remaining inadvisably unrelated. Thus, calculations using contigs as different OTUs ultimately overestimate diversity when compared to diversity calculated from species coverage. In order to compare the effect of coverage and fragmentation, we generated three sets of simulated Illumina paired-end reads with different sequencing depths. We compared different assemblies performed with RayMeta, CLC Assembly Cell, MEGAHIT, SPAdes, Meta-IDBA, SOAPdenovo, Velvet, Metavelvet, and MIRA with the best attainable assemblies for each dataset (formed by arranging data using known genome coordinates) by calculating different assembly statistics. A new fragmentation score was included to estimate the degree of genome fragmentation of each taxon and adjust the coverage accordingly. The abundance in the metagenome was compared by bootstrapping the assembly data and hierarchically clustering them with the best possible assembly. Additionally, richness and diversity indexes were calculated for all the resulting assemblies and were assessed under two distributions: contigs as independent OTUs and sequences classified by species. Finally, we search for the strongest correlations between the diversity indexes and the different assembly statistics. Although fragmentation was dependent of genome coverage, it was not as heavily influenced by the assembler. The sequencing depth was the predominant attractor that influenced the success of the assemblies. The coverage increased notoriously in larger datasets, whereas fragmentation values remained lower and unsaturated. While still far from obtaining the ideal assemblies, the RayMeta, SPAdes, and the CLC assemblers managed to build the most accurate contigs with larger datasets while Meta-IDBA showed a good performance with the medium-sized dataset, even after the adjusted coverage was calculated. Their resulting assemblies showed the highest coverage scores and the lowest fragmentation values. Alpha diversity calculated from contigs as OTUs resulted in significantly higher values for all assemblies when compared with actual species distribution, showing an overestimation due to the increased predicted abundance. Conversely, using PHACCS resulted in lower values for all assemblers. Different association methods (random-forest, generalized linear models, and the Spearman correlation index) support the number of contigs, the coverage, and fragmentation as the assembly parameters that most affect the estimation of the alpha diversity. Coverage calculations may provide an insight into relative completeness of a genome but they overlook missing fragments or overly separated sequences in a genome. The assembly of a highly fragmented genomes with high coverage may still lead to the clustering of different OTUs that are actually different fragments of a genome. Thus, it proves useful to penalize coverage with a fragmentation score. Using contigs for calculating alpha diversity result in overestimation but it is usually the only approach available. Still, it is enough for sample comparison. The best approach may be determined by choosing the assembler that better fits the sequencing depth and adjusting the parameters for longer accurate contigs whenever possible whereas diversity may be calculated considering taxonomical and genomic information if available.

Metagenomic Analysis of Crohn's Disease Patients Identifies Changes in the Virome and Microbiome Related to Disease Status and Therapy, and Detects Potential Interactions and Biomarkers.

BACKGROUND: The aim of this study was to survey the bacterial and viral communities in different types of samples from patients with Crohn's disease (CD) at different stages of the disease to relate their distribution with the origin and progression of this disorder. METHODS: A total of 42 fecal samples and 15 biopsies from 20 patients with CD and 20 healthy control individuals were collected for bacterial 16S rRNA gene profiling and DNA/RNA virome metagenomic analysis through 454 pyrosequencing. Their composition, abundance, and diversity were analyzed, and comparisons of disease status, patient status, and sample origin were used to determine statistical differences between the groups. RESULTS: Bacterial composition and relative abundance in new-onset patients with CD differed markedly from control individuals. Individual variability and sample origin had a stronger impact on viral communities than the disease, contrary to what was observed for bacterial populations although increased numbers of overrepresented viruses were observed in feces from patients with CD. Correlation-based networks were constructed to show potential relations between bacteria and between those and viruses. CONCLUSIONS: The bacterial community reflects the disease status of individuals more accurately than their viral counterparts. However, numerous viral biomarkers specifically associated with CD disease were identified. Because viruses can modulate bacterial communities, the correlation networks between both communities constitute a step forward in unraveling their interactions under normal and CD disease conditions.