Gut mucus layer degradation is associated with aggressive cervical cancer phenotype

Background Gut microbiome community composition differs between cervical cancer (CC) patients and healthy controls, and increased gut diversity is associated with improved outcomes after treatment. We proposed that functions of specific microbial species adjoining the mucus layer may directly impact the biology of CC. Results In this study, we examined metagenomes of rectal swabs in 41 CC patients using whole-genome shotgun sequencing and found a significant association between molecular functions encoded by the metagenomes with markers of aggressive cancer including initial tumor size and stage. Profiling of the molecular function abundances and their distributions identified 2 microbial communities co-existing in each metagenome but with distinct metabolism and taxonomic structures. Community A (Clostridia and Proteobacteria predominant) was characterized by high activity of pathways involved in stress response, mucus glycan degradation and utilization of degradation byproducts. This community was prevalent in larger, advanced stage tumors. Conversely, community B (Bacteroidia predominant) was characterized by fast growth, active oxidative phosphorylation, and production of vitamins. This community was prevalent in small, early-stage tumors. Conclusions Based on these results, we propose that increased mucus layer degradation is associated with a more aggressive cervical cancer phenotype.

Retrospective Genotyping and Whole Genome Sequencing of a Canine Parvovirus Outbreak in Bangladesh

Canine parvovirus 2 (CPV-2) outbreaks in close quarters such as kennels or shelters can cause substantial case fatality. Thirteen dead Labradors from a secluded kennel of security dogs presented with typical clinical signs and gross pathology of parvovirus infection. Whole genome shotgun sequencing from tissue-extracted genomic DNA detected new CPV-2a as the contributing antigenic variant. Further genotyping using polymerase chain reaction coupled with high-resolution melt assays (PCR-HRM) confirmed new CPV-2a infection in all deceased dogs. PCR-HRM of additional thirty-four clinically suspected dogs suggested that this variant is in wider community circulation, at least in the southeastern part of Bangladesh. We present complete genome sequence of the new CPV-2a variant circulating in the domestic canine population of Bangladesh.

Dynamics of the fecal microbiome and antimicrobial resistome in commercial piglets during the weaning period

This study aimed to characterize the alteration of the fecal microbiome and antimicrobial resistance (AMR) determinants in 24 piglets at day 3 pre-weaning (D. − 3), weaning day (D.0), days 3 (D.3) and 8 post-weaning (D.8), using whole-genome shotgun sequencing. Distinct clusters of microbiomes and AMR determinants were observed at D.8 when Prevotella (20.9%) was the major genus, whereas at D. − 3–D.3, Alistipes (6.9–12.7%) and Bacteroides (5.2–8.5%) were the major genera. Lactobacillus and Escherichia were notably observed at D. − 3 (1.2%) and D. − 3–D.3 (0.2–0.4%), respectively. For AMR, a distinct cluster of AMR determinants was observed at D.8, mainly conferring resistance to macrolide–lincosamide–streptogramin (mefA), β-lactam (cfxA6 and aci1) and phenicol (rlmN). In contrast, at D. − 3–D.3, a high abundance of determinants with aminoglycoside (AMG) (sat, aac(6')-aph(2''), aadA and acrF), β-lactam (fus-1, cepA and mrdA), multidrug resistance (MDR) (gadW, mdtE, emrA, evgS, tolC and mdtB), phenicol (catB4 and cmlA4), and sulfonamide patterns (sul3) was observed. Canonical correlation analysis (CCA) plot associated Escherichia coli with aac(6')-aph(2''), emrA, mdtB, catB4 and cmlA4 at D. − 3, D.0 and/or D.3 whereas at D.8 associations between Prevotella and mefA, cfxA6 and aci1 were identified. The weaning age and diet factor played an important role in the microbial community composition.

Potential of Variovorax paradoxus isolate BFB1_13 for bioremediation of BTEX contaminated sites

Here, we report and discuss the applicability of Variovorax paradoxus strain BFB1_13 in the bioremediation of BTEX contaminated sites. Strain BFB1_13 was capable of degrading all the six BTEX-compounds under both aerobic (O2 conc. 8 mg l−1) and micro-aerobic/oxygen-limited (O2 conc. 0.5 mg l−1) conditions using either individual (8 mg‧l−1) or a mixture of compounds (~ 1.3 mg‧l−1 of each BTEX compound). The BTEX biodegradation capability of SBP-encapsulated cultures (SBP—Small Bioreactor Platform) was also assessed. The fastest degradation rate was observed in the case of aerobic benzene biodegradation (8 mg l−1 per 90 h). Complete biodegradation of other BTEX occurred after at least 168 h of incubation, irrespective of the oxygenation and encapsulation. No statistically significant difference was observed between aerobic and microaerobic BTEX biodegradation. Genes involved in BTEX biodegradation were annotated and degradation pathways were predicted based on whole-genome shotgun sequencing and metabolic analysis. We conclude that V. paradoxus strain BFB1_13 could be used for the development of reactive biobarriers for the containment and in situ decontamination of BTEX contaminated groundwater plumes. Our results suggest that V. paradoxus strain BFB1_13—alone or in co-culture with other BTEX degrading bacterial isolates—can be a new and efficient commercial bioremediation agent for BTEX contaminated sites.

Comparison of 16S and whole genome dog microbiomes using machine learning

Background Recent advances in sequencing technologies have driven studies identifying the microbiome as a key regulator of overall health and disease in the host. Both 16S amplicon and whole genome shotgun sequencing technologies are currently being used to investigate this relationship, however, the choice of sequencing technology often depends on the nature and experimental design of the study. In principle, the outputs rendered by analysis pipelines are heavily influenced by the data used as input; it is then important to consider that the genomic features produced by different sequencing technologies may emphasize different results. Results In this work, we use public 16S amplicon and whole genome shotgun sequencing (WGS) data from the same dogs to investigate the relationship between sequencing technology and the captured gut metagenomic landscape in dogs. In our analyses, we compare the taxonomic resolution at the species and phyla levels and benchmark 12 classification algorithms in their ability to accurately identify host phenotype using only taxonomic relative abundance information from 16S and WGS datasets with identical study designs. Our best performing model, a random forest trained by the WGS dataset, identified a species (Bacteroides coprocola) that predominantly contributes to the abundance of leuB, a gene involved in branched chain amino acid biosynthesis; a risk factor for glucose intolerance, insulin resistance, and type 2 diabetes. This trend was not conserved when we trained the model using 16S sequencing profiles from the same dogs. Conclusions Our results indicate that WGS sequencing of dog microbiomes detects a greater taxonomic diversity than 16S sequencing of the same dogs at the species level and with respect to four gut-enriched phyla levels. This difference in detection does not significantly impact the performance metrics of machine learning algorithms after down-sampling. Although the important features extracted from our best performing model are not conserved between the two technologies, the important features extracted from either instance indicate the utility of machine learning algorithms in identifying biologically meaningful relationships between the host and microbiome community members. In conclusion, this work provides the first systematic machine learning comparison of dog 16S and WGS microbiomes derived from identical study designs.

Novel Transaminase and Laccase from Streptomyces spp. Using Combined Identification Approaches

Three Streptomyces sp. strains with a multitude of target enzymatic activities confirmed by functional screening, namely BV129, BV286 and BV333, were subjected to genome sequencing aiming at the annotation of genes of interest, in-depth bioinformatics characterization and functional expression of the biocatalysts. A whole-genome shotgun sequencing followed by de novo genome assembly and annotation was performed revealing genomes of 6.4, 9.4 and 7.3 Mbp, respectively. Functional annotation of the proteins of interest resulted in between 2047 and 2763 putative targets. Among the various enzymatic activities that the three Streptomyces strains demonstrated to produce by functional screening, we focused our attention on transaminases (TAs) and laccases due to their high biocatalytic potential. Bioinformatics search allowed the identification of a putative TA from Streptomyces sp. BV333 as a potentially novel broad substrate scope TA and a putative laccase from Streptomyces sp. BV286 as potentially novel blue multicopper oxidase. The two sequences were cloned and overexpressed in Escherichia coli and the two novel enzymes, transaminase Sbv333-TA and laccase Sbv286-LAC, were characterized. Interestingly, both enzymes resulted to be exceptionally thermostable, Sbv333-TA showing a melting temperature (TM = 85 °C) only slightly lower compared to the TM of the most thermostable transaminases described to date (87–88 °C) and Sbv286-LAC being even thermoactivated at temperature >60 °C. Moreover, Sbv333-TA showed a broad substrate scope and remarkably demonstrated to be active in the transamination of β-ketoesters, which are rarely accepted by currently known TAs. On the other hand, Sbv286-LAC showed an improved activity in the presence of the cosolvent acetonitrile. Overall, it was shown that a combination of approaches from standard microbiological and biochemical screens to genome sequencing and analysis is required to afford novel and functional biocatalysts.

A Metagenome-Wide Association Study of the Gut Microbiome and Metabolic Syndrome

Metabolic syndrome (MetS) is a wide-ranging disorder, which includes insulin resistance, altered glucose and lipid metabolism, and increased blood pressure and visceral obesity. MetS symptoms combine to result in a significant increase in cardiovascular risk. It is therefore critical to treat MetS in the early stages of the disorder. In this study, 123 MetS patients and 304 controls were recruited to determine whether the gut microbiome plays a role in MetS development and progression. By using whole-genome shotgun sequencing, we found that the gut microbiomes of MetS patients were different from those of controls, with MetS patients possessing significantly lower gut microbiome diversity. In addition, 28 bacterial species were negatively correlated with waist circumstance, with Alistipes onderdonkii showing the strongest correlation, followed by Bacteroides thetaiotaomicron, Clostridium asparagiforme, Clostridium citroniae, Clostridium scindens, and Roseburia intestinalis. These species were also enriched in controls relative to MetS patients. In addition, pathways involved in the biosynthesis of carbohydrates, fatty acids, and lipids were enriched in the MetS group, indicating that microbial functions related to fermentation may play a role in MetS. We also found that microbiome changes in MetS patients may aggravate inflammation and contribute to MetS diseases by inhibiting the production of short-chain fatty acids (SCFAs). Taken together, these results indicate the potential utility of beneficial gut microbiota as a potential therapeutic to alleviate MetS.

HolistIC: Leveraging Hi-C and Whole Genome Shotgun Sequencing for Double Minute Chromosome Discovery

Double minute chromosomes are acentric extrachromosomal DNA artifacts that are frequently observed in the cells of numerous cancers. They are highly amplified and contain oncogenes and drug resistance genes, making their presence a challenge for effective cancer treatment. Algorithmic discovery of double minutes (DM) can potentially improve bench-derived therapies for cancer treatment. A hindrance to this task is that DMs evolve, yielding circular chromatin that shares segments from progenitor double minutes. This creates double minutes with overlapping amplicon coordinates. Existing DM discovery algorithms use whole genome shotgun sequencing in isolation, which can potentially incorrectly classify DMs that share overlapping coordinates. In this study, we describe an algorithm called “ HolistIC” that can predict double minutes in tumor genomes by integrating whole genome shotgun sequencing (WGS) and Hi-C sequencing data. The consolidation of these sources of information resolves ambiguity in double minute amplicon prediction that exists in DM prediction with WGS data used in isolation. We implemented and tested our algorithm on the tandem Hi-C and WGS datasets of three cancer datasets and a simulated dataset. Results on the cancer datasets demonstrated HolistIC’s ability to predict DMs from Hi-C and WGS data in tandem. The results on the simulated data showed the HolistIC can accurately distinguish double minutes that have overlapping amplicon coordinates, an advance over methods that predict extrachromosomal amplification using WGS data in isolation.AvailabilityOur software is available at http://www.github.com/mhayes20/HolistIC.

A Chromosome-Level Genome Assembly of the Anglerfish Lophius litulon

Anglerfishes are a highly diverse group of species with unique characteristics. Here, we report the first chromosome-level genome of a species in the order Lophiiformes, the yellow goosefish (Lophius litulon), obtained by whole genome shotgun sequencing and high-throughput chromatin conformation capture. Approximately 97.20% of the assembly spanning 709.23 Mb could be anchored to 23 chromosomes with a contig N50 of 164.91 kb. The BUSCO value was 95.4%, suggesting that the quality of the assembly was high. A comparative gene family analysis identified expanded and contracted gene families, and these may be associated with adaptation to the benthic environment and the lack of scales in the species. A majority of positively selected genes were related to metabolic processes, suggesting that digestive and metabolic system evolution expanded the diversity of yellow goosefish prey. Our study provides a valuable genetic resource for understanding the mechanisms underlying the unique features of the yellow goosefish and for investigating anglerfish evolution.