metaSNV v2: detection of SNVs and subspecies in prokaryotic metagenomes

Bifidobacterium and Lactobacillus Probiotics and Gut Dysbiosis in Preterm Infants: The PRIMAL Randomized Clinical Trial

Importance

The effects of probiotic interventions on colonization with resistant bacteria and early microbiome development in preterm infants remain to be clarified.

Objective

To examine the efficacy of Bifidobacterium longum subsp infantis, Bifidobacterium animalis subsp lactis (BB-12), and Lactobacillus acidophilus (La-5) probiotics to prevent colonization with multidrug-resistant organisms or highly epidemic bacteria (MDRO+) and to shape the microbiome of preterm infants toward the eubiotic state of healthy full-term infants.

Design, Setting, and Participants

The multicenter, double-blinded, placebo-controlled, group sequential, phase 3 Priming Immunity at the Beginning of Life (PRIMAL) randomized clinical trial, conducted from April 2018 to June 2020, included infants with gestational age of 28 to 32 weeks at 18 German neonatal units. Data analyses were conducted from March 2020 to August 2023.

Intervention

A total of 28 days of multistrain probiotics diluted in human milk/formula starting within the first 72 hours of life.

Main Outcomes and Measures

Colonization with MDRO+ at day 30 of life (primary end point), late-onset sepsis and severe gastrointestinal complication (safety end points), and gut dysbiosis, ie, deviations from the microbiome of healthy, term infants (eubiosis score) based on 16-subunit ribosomal RNA and metagenomic sequencing.

Results

Among the 643 infants randomized until the stop of recruitment based on interim results, 618 (median [IQR] gestational age, 31.0 [29.7-32.1] weeks; 333 male [53.9%]; mean [SD] birth weight, 1502 [369] g) had follow-up at day 30. The interim analysis with all available data from 219 infants revealed MDRO+ colonization in 43 of 115 infants (37.4%) in the probiotics group and in 39 of 104 infants (37.5%) in the control group (adjusted risk ratio, 0.99; 95% CI, 0.54-1.81; P = .97). Safety outcomes were similar in both groups, ie, late-onset sepsis (probiotics group: 8 of 316 infants [2.5%]; control group: 12 of 322 infants [3.7%]) and severe gastrointestinal complications (probiotics group: 6 of 316 infants [1.9%]; control group: 7 of 322 infants [2.2%]). The probiotics group had higher eubiosis scores than the control group at the genus level (254 vs 258 infants; median scores, 0.47 vs 0.41; odds ratio [OR], 1.07; 95% CI, 1.02-1.13) and species level (96 vs 83 infants; median scores, 0.87 vs 0.59; OR, 1.28; 95% CI, 1.19-1.38). Environmental uptake of the B infantis probiotic strain in the control group was common (41 of 84 [49%]), which was highly variable across sites and particularly occurred in infants with a sibling who was treated with probiotics.

Conclusions and Relevance

Multistrain probiotics did not reduce the incidence of MDRO+ colonization at day 30 of life in preterm infants but modulated their microbiome toward eubiosis.

Trial Registration

German Clinical Trials Register: DRKS00013197.

Decoding populations in the ocean microbiome

Understanding the characteristics and structure of populations is fundamental to comprehending ecosystem processes and evolutionary adaptations. While the study of animal and plant populations has spanned a few centuries, microbial populations have been under scientific scrutiny for a considerably shorter period. In the ocean, analyzing the genetic composition of microbial populations and their adaptations to multiple niches can yield important insights into ecosystem function and the microbiome's response to global change. However, microbial populations have remained elusive to the scientific community due to the challenges associated with isolating microorganisms in the laboratory. Today, advancements in large-scale metagenomics and metatranscriptomics facilitate the investigation of populations from many uncultured microbial species directly from their habitats. The knowledge acquired thus far reveals substantial genetic diversity among various microbial species, showcasing distinct patterns of population differentiation and adaptations, and highlighting the significant role of selection in structuring populations. In the coming years, population genomics is expected to significantly increase our understanding of the architecture and functioning of the ocean microbiome, providing insights into its vulnerability or resilience in the face of ongoing global change. Video Abstract.

Insights into gut microbiomes in stem cell transplantation by comprehensive shotgun long-read sequencing

The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics.

Pitfalls of genotyping microbial communities with rapidly growing genome collections

Detecting genetic variants in metagenomic data is a priority for understanding the evolution, ecology, and functional characteristics of microbial communities. Many tools that perform this metagenotyping rely on aligning reads of unknown origin to a database of sequences from many species before calling variants. In this synthesis, we investigate how databases of increasingly diverse and closely related species have pushed the limits of current alignment algorithms, thereby degrading the performance of metagenotyping tools. We identify multi-mapping reads as a prevalent source of errors and illustrate a trade-off between retaining correct alignments versus limiting incorrect alignments, many of which map reads to the wrong species. Then we evaluate several actionable mitigation strategies and review emerging methods showing promise to further improve metagenotyping in response to the rapid growth in genome collections. Our results have implications beyond metagenotyping to the many tools in microbial genomics that depend upon accurate read mapping.

proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.

MIDAS2: Metagenomic Intra-species Diversity Analysis System

SUMMARY

The Metagenomic Intra-Species Diversity Analysis System (MIDAS) is a scalable metagenomic pipeline that identifies single nucleotide variants (SNVs) and gene copy number variants in microbial populations. Here, we present MIDAS2, which addresses the computational challenges presented by increasingly large reference genome databases, while adding functionality for building custom databases and leveraging paired-end reads to improve SNV accuracy. This fast and scalable reengineering of the MIDAS pipeline enables thousands of metagenomic samples to be efficiently genotyped.

AVAILABILITY AND IMPLEMENTATION

The source code is available at https://github.com/czbiohub/MIDAS2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables

The Metagenomic Intra-Species Diversity Analysis System 2 (MIDAS2) is a scalable pipeline that identifies single nucleotide variants and gene copy number variants in metagenomes using comprehensive reference databases built from public microbial genome collections (metagenotyping). MIDAS2 is the first metagenotyping tool with functionality to control metagenomic read mapping filters and to customize the reference database to the microbial community, features that improve the precision and recall of detected variants. In this article we present four basic protocols for the most common use cases of MIDAS2, along with supporting protocols for installation and use. In addition, we provide in-depth guidance on adjusting command line parameters, editing the reference database, optimizing hardware utilization, and understanding the metagenotyping results. All the steps of metagenotyping, from raw sequencing reads to population genetic analysis, are demonstrated with example data in two downloadable sequencing libraries of single-end metagenomic reads representing a mixture of multiple bacterial species. This set of protocols empowers users to accurately genotype hundreds of species in thousands of samples, providing rich genetic data for studying the evolution and strain-level ecology of microbial communities. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Species prescreening Basic Protocol 2: Download MIDAS reference database Basic Protocol 3: Population single nucleotide variant calling Basic Protocol 4: Pan-genome copy number variant calling Support Protocol 1: Installing MIDAS2 Support Protocol 2: Command line inputs Support Protocol 3: Metagenotyping with a custom collection of genomes Support Protocol 4: Metagenotyping with advanced parameters.

Recent insights into the role of microbiome in the pathogenesis of obesity

Obesity is a risk factor for many chronic diseases and its rising prevalence the last couple of decades is a healthcare concern in many countries. Obesity is a multifactorial problem that is not only limited in its causation by diet and lack of exercise. Genetics but also environmental factors such as the gut microbiome should similarly be taken into account. A plethora of articles have been published, that from various different angles, attempt to disentangle the complex interaction between gut microbiota and obesity. Examples range from the effect of the gut microbiota on the host immune system to the pathophysiological pathways in which microbial-derived metabolites affect obesity. Various discordant gut microbiota findings are a result of this complexity. In this review, in addition to summarizing the classical role of the gut microbiome in the pathogenesis of obesity, we attempt to view both the healthy and obesogenic effects of the gut microbiota as a consequence of the presence or absence of collective guilds/trophic networks. Lastly, we propose avenues and strategies for the future of gut microbiome research concerning obesity.