Reduced metagenome sequencing for strain-resolution taxonomic profiles

Readsynth: short-read simulation for consideration of composition-biases in reduced metagenome sequencing approaches

BACKGROUND

The application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates.

RESULTS

Through the development and application of simulation software, readsynth, we compare simulated metagenomic sequencing libraries with existing RMS data to assess the influence of multiple library preparation and sequencing steps on downstream analytical results. Based on read depth per position, readsynth achieved 0.79 Pearson's correlation and 0.94 Spearman's correlation to these benchmarks. Application of a novel estimation approach, fixed length taxonomic ratios, improved quantification accuracy of simulated human gut microbial communities when compared to estimates of mean or median coverage.

CONCLUSIONS

We investigate the possible strengths and weaknesses of applying the RMS technique to profiling microbial communities via simulations with readsynth. The choice of restriction enzymes and size selection steps in library prep are non-trivial decisions that bias downstream profiling and quantification. The simulations investigated in this study illustrate the possible limits of preparing metagenomic libraries with a reduced representation sequencing approach, but also allow for the development of strategies for producing and handling the sequence data produced by this promising application.

Inference of disease-associated microbial gene modules based on metagenomic and metatranscriptomic data

The identification of microbial characteristics associated with diseases is crucial for disease diagnosis and therapy. However, the presence of heterogeneity, high dimensionality, and large amounts of microbial data presents tremendous challenges in discovering key microbial features. In this paper, we present IDAM, a novel computational method for inferring disease-associated gene modules from metagenomic and metatranscriptomic data. This method integrates gene context conservation (uber-operons) and regulatory mechanisms (gene co-expression patterns) within a mathematical graph model to explore gene modules associated with specific diseases. It alleviates reliance on prior meta-data. We applied IDAM to publicly available datasets from inflammatory bowel disease, melanoma, type 1 diabetes mellitus, and irritable bowel syndrome. The results demonstrated the superior performance of IDAM in inferring disease-associated characteristics compared to existing popular tools. Furthermore, we showcased the high reproducibility of the gene modules inferred by IDAM using independent cohorts with inflammatory bowel disease. We believe that IDAM can be a highly advantageous method for exploring disease-associated microbial characteristics. The source code of IDAM is freely available at https://github.com/OSU-BMBL/IDAM, and the web server can be accessed at https://bmblx.bmi.osumc.edu/idam/.

Applications of microbiology to different forensic scenarios - A narrative review

In contrast to other forensic disciplines, forensic microbiology is still too often considered a "side activity" and is not able to make a real and concrete contribution to forensic investigations. Indeed, the various application aspects of this discipline still remain a niche activity and, as a result, microbiological investigations are often omitted or only approximated, in part due to poor report in the literature. However, in certain situations, forensic microbiology can prove to be extremely effective, if not crucial, when all other disciplines fail. Precisely because microorganisms can represent forensic evidence, in this narrative review all the major pathological forensic applications described in the literature have been presented. The goal of our review is to highlight the versatility and transversality of microbiology in forensic science and to provide a comprehensive source of literature to refer to when needed.

A Globally Distributed Bacteroides caccae Strain Is the Most Prevalent Mother-Child Shared Bacteroidaceae Strain in a Large Scandinavian Cohort

Bacteroides and Phocaeicola, members of the family Bacteroidaceae, are among the first microbes to colonize the human infant gut. While it is known that these microbes can be transmitted from mother to child, our understanding of the specific strains that are shared and potentially transmitted is limited. In this study, we aimed to investigate the shared strains of Bacteroides and Phocaeicola in mothers and their infants. We analyzed fecal samples from pregnant woman recruited at 18 weeks of gestation from the PreventADALL study, as well as offspring samples from early infancy, including skin swab samples taken within 10 min after birth, the first available fecal sample (meconium), and fecal samples at 3 months of age. We screened 464 meconium samples for Bacteroidaceae, with subsequent selection of 144 mother-child pairs for longitudinal analysis, based on the presence of Bacteroidaceae, longitudinal sample availability, and delivery mode. Our results showed that Bacteroidaceae members were mainly detected in samples from vaginally delivered infants. We identified high prevalences of Phocaeicola vulgatus, Phocaeicola dorei, Bacteroides caccae, and Bacteroides thetaiotaomicron in mothers and vaginally born infants. However, at the strain level, we observed high prevalences of only two strains: a B. caccae strain and a P. vulgatus strain. Notably, the B. caccae strain was identified as a novel component of mother-child shared strains, and its high prevalence was also observed in publicly available metagenomes worldwide. Our findings suggest that mode of delivery may play a role in shaping the early colonization of the infant gut microbiota, in particular the colonization of Bacteroidaceae members. IMPORTANCE Our study provides evidence that Bacteroidaceae strains present on infants' skin within 10 min after birth, in meconium samples, and in fecal samples at 3 months of age in vaginally delivered infants are shared with their mothers. Using strain resolution analyses, we identified two strains, belonging to Bacteroides caccae and Phocaeicola vulgatus, as shared between mothers and their infants. Interestingly, the B. caccae strain showed a high prevalence worldwide, while the P. vulgatus strain was less common. Our findings also showed that vaginal delivery was associated with early colonization of Bacteroidaceae members, whereas cesarean section delivery was associated with delayed colonization. Given the potential for these microbes to influence the colonic environment, our results suggest that understanding the bacterial-host relationship at the strain level may have implications for infant health and development later in life.

The microbiota as a modulator of mucosal inflammation and HIV/HPV pathogenesis: From association to causation

Although the microbiota has largely been associated with the pathogenesis of viral infections, most studies using omics techniques are correlational and hypothesis-generating. The mechanisms affecting the immune responses to viral infections are still being fully understood. Here we focus on the two most important sexually transmitted persistent viruses, HPV and HIV. Sophisticated omics techniques are boosting our ability to understand microbiota-pathogen-host interactions from a functional perspective by surveying the host and bacterial protein and metabolite production using systems biology approaches. However, while these strategies have allowed describing interaction networks to identify potential novel microbiota-associated biomarkers or therapeutic targets to prevent or treat infectious diseases, the analyses are typically based on highly dimensional datasets -thousands of features in small cohorts of patients-. As a result, we are far from getting to their clinical use. Here we provide a broad overview of how the microbiota influences the immune responses to HIV and HPV disease. Furthermore, we highlight experimental approaches to understand better the microbiota-host-virus interactions that might increase our potential to identify biomarkers and therapeutic agents with clinical applications.

Diversity and functional analysis of rumen and fecal microbial communities associated with dietary changes in crossbreed dairy cattle

The objective of this study was to investigate the effect of varying roughage and concentrate proportions, in diet of crossbreed dairy cattle, on the composition and associated functional genes of rumen and fecal microbiota. We also explored fecal samples as a proxy for rumen liquor samples. Six crossbred dairy cattle were reared on three diets with an increasing concentrate and reducing roughage amount in three consecutive 10-day periods. After each period, individual rumen liquor and fecal samples were collected and analyzed through shotgun metagenomic sequencing. Average relative abundance of identified Operational Taxonomic Units (OTU) and microbial functional roles from all animals were compared between diets and sample types (fecal and rumen liquor). Results indicated that dietary modifications significantly affected several rumen and fecal microbial OTUs. In the rumen, an increase in dietary concentrate resulted in an upsurge in the abundance of Proteobacteria, while reducing the proportions of Bacteroidetes and Firmicutes. Conversely, changes in microbial composition in fecal samples were not consistent with dietary modification patterns. Microbial functional pathway classification identified that carbohydrate metabolism and protein metabolism pathways dominated microbial roles. Assessment of dietary effects on the predicted functional roles of these microbiota revealed that a high amount of dietary concentrate resulted in an increase in central carbohydrate metabolism and a corresponding reduction in protein synthesis. Moreover, we identified several microbial stress-related responses linked to dietary changes. Bacteroides and Clostridium genera were the principal hosts of these microbial functions. Therefore, the roughage to concentrate proportion has more influence on the microbial composition and microbial functional genes in rumen samples than fecal samples. As such, we did not establish a significant relationship between the rumen and fecal metagenome profiles, and the rumen and fecal microbiota from one animal did not correlate more than those from different animals.

High-resolution shotgun metagenomics: the more data, the better?

In shotgun metagenomics (SM), the state-of-the-art bioinformatic workflows are referred to as high-resolution shotgun metagenomics (HRSM) and require intensive computing and disk storage resources. While the increase in data output of the latest iteration of high-throughput DNA sequencing systems can allow for unprecedented sequencing depth at a minimal cost, adjustments in HRSM workflows will be needed to properly process these ever-increasing sequence datasets. One potential adaptation is to generate so-called shallow SM datasets that contain fewer sequencing data per sample as compared with the more classic high coverage sequencing. While shallow sequencing is a promising avenue for SM data analysis, detailed benchmarks using real-data are lacking. In this case study, we took four public SM datasets, one massive and the others moderate in size and subsampled each dataset at various levels to mimic shallow sequencing datasets of various sequencing depths. Our results suggest that shallow SM sequencing is a viable avenue to obtain sound results regarding microbial community structures and that high-depth sequencing does not bring additional elements for ecological interpretation. More specifically, results obtained by subsampling as little as 0.5 M sequencing clusters per sample were similar to the results obtained with the largest subsampled dataset for human gut and agricultural soil datasets. For an Antarctic dataset, which contained only a few samples, 4 M sequencing clusters per sample was found to generate comparable results to the full dataset. One area where ultra-deep sequencing and maximizing the usage of all data was undeniably beneficial was in the generation of metagenome-assembled genomes.

Exploration of the presence and abundance of multidrug resistance efflux genes in oil and gas environments

As sequencing technology improves and the cost of metagenome sequencing decreases, the number of sequenced environments increases. These metagenomes provide a wealth of data in the form of annotated and unannotated genes. The role of multidrug resistance efflux pumps (MDREPs) is the removal of antibiotics, biocides and toxic metabolites created during aromatic hydrocarbon metabolism. Due to their naturally occurring role in hydrocarbon metabolism and their role in biocide tolerance, MDREP genes are of particular importance for the protection of pipeline assets. However, the heterogeneity of MDREP genes creates a challenge during annotation and detection. Here we use a selection of primers designed to target MDREPs in six pure species and apply them to publicly available metagenomes associated with oil and gas environments. Using in silico PCR with relaxed primer binding conditions we probed the metagenomes of a shale reservoir, a heavy oil tailings pond, a civil wastewater treatment, two marine sediments exposed to hydrocarbons following the Deepwater Horizon oil spill and a non-exposed marine sediment to assess the presence and abundance of MDREP genes. Through relaxed primer binding conditions during in silico PCR, the prevalence of MDREPs was determined. The percentage of nucleotide sequences identified by the MDREP primers was partially augmented by exposure to hydrocarbons in marine sediment and in shale reservoir compared to hydrocarbon-free marine sediments while tailings ponds and wastewater had the highest percentages. We believe this approach lays the groundwork for a supervised method of identifying poorly conserved genes within metagenomes.

Gut microbial metabolome in inflammatory bowel disease: From association to therapeutic perspectives

Inflammatory bowel disease (IBD), comprising Crohn's disease (CD) and ulcerative colitis (UC), is a set of clinically chronic, relapsing gastrointestinal inflammatory disease and lacks of an absolute cure. Although the precise etiology is unknown, developments in high-throughput microbial genomic sequencing significantly illuminate the changes in the intestinal microbial structure and functions in patients with IBD. The application of microbial metabolomics suggests that the microbiota can influence IBD pathogenesis by producing metabolites, which are implicated as crucial mediators of host-microbial crosstalk. This review aims to elaborate the current knowledge of perturbations of the microbiome-metabolome interface in IBD with description of altered composition and metabolite profiles of gut microbiota. We emphasized and elaborated recent findings of several potentially protective metabolite classes in IBD, including fatty acids, amino acids and derivatives and bile acids. This article will facilitate a deeper understanding of the new therapeutic approach for IBD by applying metabolome-based adjunctive treatment.

The effect of carbon-based copper nanocomposites on Microcystis aeruginosa and the movability of antibiotic resistance genes in urban water

The presence of Microcystis aeruginosa (M. aeruginosa) can affect the transference of antibiotic resistance genes (ARGs), and the presence of carbon-based copper nanocomposites (CCN) can affect the growth of M. aeruginosa. However, the effect of CCN on M. aeruginosa and ARGs is not fully understood. In this study, metagenomic sequencing was employed to analyze the movability of ARGs, their potential transfer, and possible hosts in photobioreactor treating urban water. The results uggested that 20 mg/L of CCN changed the composition and abundance of microorganisms in urban water, significantly promoted the flocculation of M aeruginosa, and decreased the composing proportion of Cyanophyta sp. and M aeruginosa. The results indicated that 20 mg/L of CCN significantly decreased the absolute abundance and ARGs proportions which mediated by plasmids (32.7 %). Furthermore, the lower co-occurrence probability of ARGs and mobile genetic elements (MGEs) suggested that 20 mg/L of CCN weakened the movability potential of ARGs mediated by MGEs such as plasmids. Among the 452 metagenome-assembled genomes (MAGs), 95 MAGs belonging to 41 bacterial categories were identified as possible ARG hosts. These results will provide insights into the control of harmful cyanobacteria and the management of ARGs in urban water.

Plant-Microbe Interaction: Aboveground to Belowground, from the Good to the Bad

Soil health and fertility issues are constantly addressed in the agricultural industry. Through the continuous and prolonged use of chemical heavy agricultural systems, most agricultural lands have been impacted, resulting in plateaued or reduced productivity. As such, to invigorate the agricultural industry, we would have to resort to alternative practices that will restore soil health and fertility. Therefore, in recent decades, studies have been directed towards taking a Magellan voyage of the soil rhizosphere region, to identify the diversity, density, and microbial population structure of the soil, and predict possible ways to restore soil health. Microbes that inhabit this region possess niche functions, such as the stimulation or promotion of plant growth, disease suppression, management of toxicity, and the cycling and utilization of nutrients. Therefore, studies should be conducted to identify microbes or groups of organisms that have assigned niche functions. Based on the above, this article reviews the aboveground and below-ground microbiomes, their roles in plant immunity, physiological functions, and challenges and tools available in studying these organisms. The information collected over the years may contribute toward future applications, and in designing sustainable agriculture.

HumGut: a comprehensive human gut prokaryotic genomes collection filtered by metagenome data

BACKGROUND

A major bottleneck in the use of metagenome sequencing for human gut microbiome studies has been the lack of a comprehensive genome collection to be used as a reference database. Several recent efforts have been made to re-construct genomes from human gut metagenome data, resulting in a huge increase in the number of relevant genomes. In this work, we aimed to create a collection of the most prevalent healthy human gut prokaryotic genomes, to be used as a reference database, including both MAGs from the human gut and ordinary RefSeq genomes.

RESULTS

We screened > 5,700 healthy human gut metagenomes for the containment of > 490,000 publicly available prokaryotic genomes sourced from RefSeq and the recently announced UHGG collection. This resulted in a pool of > 381,000 genomes that were subsequently scored and ranked based on their prevalence in the healthy human metagenomes. The genomes were then clustered at a 97.5% sequence identity resolution, and cluster representatives (30,691 in total) were retained to comprise the HumGut collection. Using the Kraken2 software for classification, we find superior performance in the assignment of metagenomic reads, classifying on average 94.5% of the reads in a metagenome, as opposed to 86% with UHGG and 44% when using standard Kraken2 database. A coarser HumGut collection, consisting of genomes dereplicated at 95% sequence identity-similar to UHGG, classified 88.25% of the reads. HumGut, half the size of standard Kraken2 database and directly comparable to the UHGG size, outperforms them both.

CONCLUSIONS

The HumGut collection contains > 30,000 genomes clustered at a 97.5% sequence identity resolution and ranked by human gut prevalence. We demonstrate how metagenomes from IBD-patients map equally well to this collection, indicating this reference is relevant also for studies well outside the metagenome reference set used to obtain HumGut. All data and metadata, as well as helpful code, are available at http://arken.nmbu.no/~larssn/humgut/ . Video Abstract.