Understanding Horizontal Gene Transfer network in human gut microbiota

Enhancing insights into diseases through horizontal gene transfer event detection from gut microbiome

Horizontal gene transfer (HGT) phenomena pervade the gut microbiome and significantly impact human health. Yet, no current method can accurately identify complete HGT events, including the transferred sequence and the associated deletion and insertion breakpoints from shotgun metagenomic data. Here, we develop LocalHGT, which facilitates the reliable and swift detection of complete HGT events from shotgun metagenomic data, delivering an accuracy of 99.4%-verified by Nanopore data-across 200 gut microbiome samples, and achieving an average F1 score of 0.99 on 100 simulated data. LocalHGT enables a systematic characterization of HGT events within the human gut microbiome across 2098 samples, revealing that multiple recipient genome sites can become targets of a transferred sequence, microhomology is enriched in HGT breakpoint junctions (P-value = 3.3e-58), and HGTs can function as host-specific fingerprints indicated by the significantly higher HGT similarity of intra-personal temporal samples than inter-personal samples (P-value = 4.3e-303). Crucially, HGTs showed potential contributions to colorectal cancer (CRC) and acute diarrhoea, as evidenced by the enrichment of the butyrate metabolism pathway (P-value = 3.8e-17) and the shigellosis pathway (P-value = 5.9e-13) in the respective associated HGTs. Furthermore, differential HGTs demonstrated promise as biomarkers for predicting various diseases. Integrating HGTs into a CRC prediction model achieved an AUC of 0.87.

The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients

Background

While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated.

Methods

Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use.

Results

Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation.

Conclusion

This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.

Gut microbial network signatures of early colonizers in preterm neonates with extrauterine growth restriction

BACKGROUND

Extrauterine growth restriction (EUGR) represents a prevalent condition observed in preterm neonates, which poses potential adverse implications for both neonatal development and long-term health outcomes. The manifestation of EUGR has been intricately associated with perturbations in microbial and metabolic profiles. This study aimed to investigate the characteristics of the gut microbial network in early colonizers among preterm neonates with EUGR.

METHODS

Twenty-nine preterm infants participated in this study, comprising 14 subjects in the EUGR group and 15 in the normal growth (AGA) group. Meconium (D1) and fecal samples were collected at postnatal day 28 (D28) and 1 month after discharge (M1). Subsequently, total bacterial DNA was extracted and sequenced using the Illumina MiSeq system, targeting the V3-V4 hyper-variable regions of the 16S rRNA gene.

RESULTS

The outcomes of principal coordinates analysis (PCoA) and examination of the microbial network structure revealed distinctive developmental trajectories in the gut microbiome during the initial three months of life among preterm neonates with and without EUGR. Significant differences in microbial community were observed at the D1 (P = 0.039) and M1 phases (P = 0.036) between the EUGR and AGA groups, while a comparable microbial community was noted at the D28 phase (P = 0.414). Moreover, relative to the AGA group, the EUGR group exhibited significantly lower relative abundances of bacteria associated with secretion of short-chain fatty acids, including Lactobacillus (P = 0.041) and Parabacteroides (P = 0.033) at the D1 phase, Bifidobacterium at the D28 phase, and genera Dysgonomonas (P = 0.042), Dialister (P = 0.02), Dorea (P = 0.042), and Fusobacterium (P = 0.017) at the M1 phase.

CONCLUSION

Overall, the present findings offer crucial important insights into the distinctive gut microbial signatures exhibited by earlier colonizers in preterm neonates with EUGR. Further mechanistic studies are needed to establish whether these differences are the cause or a consequence of EUGR.

Horizontal gene transfer after faecal microbiota transplantation in adolescents with obesity

BACKGROUND

Horizontal gene transfer (HGT) describes the transmission of DNA outside of direct ancestral lineages. The process is best characterised within the bacterial kingdom and can enable the acquisition of genetic traits that support bacterial adaptation to novel niches. The adaptation of bacteria to novel niches has particular relevance for faecal microbiota transplantation (FMT), a therapeutic procedure which aims to resolve gut-related health conditions of individuals, through transplanted gut microbiota from healthy donors.

RESULTS

Three hundred eighty-one stool metagenomic samples from a placebo-controlled FMT trial for obese adolescents (the Gut Bugs Trial) were analysed for HGT, using two complementary methodologies. First, all putative HGT events, including historical HGT signatures, were quantified using the bioinformatics application WAAFLE. Second, metagenomic assembly and gene clustering were used to assess and quantify donor-specific genes transferred to recipients following the intervention. Both methodologies found no difference between the level of putative HGT events in the gut microbiomes of FMT and placebo recipients, post-intervention. HGT events facilitated by engrafted donor species in the FMT recipient gut at 6 weeks post-intervention were identified and characterised. Bacterial strains contributing to this subset of HGT events predominantly belonged to the phylum Bacteroidetes. Engraftment-dependent horizontally transferred genes were retained within recipient microbiomes at 12 and 26 weeks post-intervention.

CONCLUSION

Our study suggests that novel microorganisms introduced into the recipient gut following FMT have no impact on the basal rate of HGT within the human gut microbiome. Analyses of further FMT studies are required to assess the generalisability of this conclusion across different FMT study designs and for the treatment of different gut-related conditions. Video Abstract.

High Diversity but Monodominance of Multidrug-Resistant Bacteria in Immunocompromised Pediatric Patients with Acute Lymphoblastic Leukemia Developing GVHD Are Not Associated with Changes in Gut Mycobiome

Graft-versus-host disease (GvHD) is a severe complication after hematopoietic stem cell transplantation (HSCT). Our study focused on identifying multidrug-resistant (MDR) gut bacteria associated with GvHD-prone guts and association with gut microbiota (GM) diversity, bacteriome, and mycobiome composition in post-HSCT patients. We examined 11 pediatric patients with acute lymphoblastic leukemia (ALL), including six with GvHD, within three time points: seven days pre-HSCT, seven days post-, and 28 days post-HSCT. The gut microbiome and its resistome were investigated using metagenomic sequencing, taxonomically classified with Kraken2, and statistically evaluated for significance using appropriate tests. We observed an increase in the abundance of MDR bacteria, mainly Enterococcus faecium strains carrying msr(C), erm(T), aac(6')-li, dfrG, and ant(6)-la genes, in GvHD patients one week post-HSCT. Conversely, non-GvHD patients had more MDR beneficial bacteria pre-HSCT, promoting immunosurveillance, with resistance genes increasing one-month post-HSCT. MDR beneficial bacteria included the anti-inflammatory Bacteroides fragilis, Ruminococcus gnavus, and Turicibacter, while most MDR bacteria represented the dominant species of GM. Changes in the gut mycobiome were not associated with MDR bacterial monodominance or GvHD. Significant α-diversity decline (Shannon index) one week and one month post-HSCT in GvHD patients (p < 0.05) was accompanied by increased Pseudomonadota and decreased Bacteroidota post-HSCT. Our findings suggest that MDR commensal gut bacteria may preserve diversity and enhance immunosurveillance, potentially preventing GvHD in pediatric ALL patients undergoing HSCT. This observation has therapeutic implications.

Profiling novel lateral gene transfer events in the human microbiome

Lateral gene transfer (LGT) is an important mechanism for genome diversification in microbial populations, including the human microbiome. While prior work has surveyed LGT events in human-associated microbial isolate genomes, the scope and dynamics of novel LGT events arising in personal microbiomes are not well understood, as there are no widely adopted computational methods to detect, quantify, and characterize LGT from complex microbial communities. We addressed this by developing, benchmarking, and experimentally validating a computational method (WAAFLE) to profile novel LGT events from assembled metagenomes. Applying WAAFLE to >2K human metagenomes from diverse body sites, we identified >100K putative high-confidence but previously uncharacterized LGT events (~2 per assembled microbial genome-equivalent). These events were enriched for mobile elements (as expected), as well as restriction-modification and transport functions typically associated with the destruction of foreign DNA. LGT frequency was quantifiably influenced by biogeography, the phylogenetic similarity of the involved taxa, and the ecological abundance of the donor taxon. These forces manifest as LGT networks in which hub species abundant in a community type donate unequally with their close phylogenetic neighbors. Our findings suggest that LGT may be a more ubiquitous process in the human microbiome than previously described. The open-source WAAFLE implementation, documentation, and data from this work are available at http://huttenhower.sph.harvard.edu/waafle.

A comprehensive review on infant formula: nutritional and functional constituents, recent trends in processing and its impact on infants' gut microbiota

Human milk is considered the most valuable form of nutrition for infants for their growth, development and function. So far, there are still some cases where feeding human milk is not feasible. As a result, the market for infant formula is widely increasing, and formula feeding become an alternative or substitute for breastfeeding. The nutritional value of the formula can be improved by adding functional bioactive compounds like probiotics, prebiotics, human milk oligosaccharides, vitamins, minerals, taurine, inositol, osteopontin, lactoferrin, gangliosides, carnitine etc. For processing of infant formula, diverse thermal and non-thermal technologies have been employed. Infant formula can be either in powdered form, which requires reconstitution with water or in ready-to-feed liquid form, among which powder form is readily available, shelf-stable and vastly marketed. Infants' gut microbiota is a complex ecosystem and the nutrient composition of infant formula is recognized to have a lasting effect on it. Likewise, the gut microbiota establishment closely parallels with host immune development and growth. Therefore, it must be contemplated as an important factor for consideration while developing formulas. In this review, we have focused on the formulation and manufacturing of safe and nutritious infant formula equivalent to human milk or aligning with the infant's needs and its ultimate impact on infants' gut microbiota.

Genome-centric metagenomics insights into functional divergence and horizontal gene transfer of denitrifying bacteria in anammox consortia

Denitrifying bacteria with high abundances in anammox communities play crucial roles in achieving stable anammox-based systems. Despite the relative constant composition of denitrifying bacteria, their functional diversity remains to be explored in anammox communities. Herein, a total of 77 high-quality metagenome-assembled genomes (MAGs) of denitrifying bacteria were recovered from the anammox community in a full-scale swine wastewater treatment plant. Among these microbes, a total of 26 MAGs were affiliated with the seven dominant denitrifying genera that have total abundances higher than 1%. A meta-analysis of these species suggested that external organics reduced the abundances of genus Ignavibacterium and species MAG.305 of UTPRO2 in anammox communities. Comparative genome analysis revealed functional divergence across different denitrifying bacteria, largely owing to their distinct capabilities for carbohydrate (including endogenous and exogenous) utilization and vitamin (e.g., pantothenate and thiamine) biosynthesis. Serval microbes in this system contained fewer genes encoding biotin, pantothenate and methionine biosynthesis compared with their related species from other habitats. In addition, the genes encoding energy production and conversion (73 genes) and inorganic ion transport (53 genes) putatively transferred from other species to denitrifying bacteria, while these denitrifying bacteria (especially genera UTPRO2 and SCN-69-89) likely donated the genes encoding nutrients (e.g., inorganic ion and amino acid) transporter (64 genes) for other members to utilize new metabolites. Collectively, these findings highlighted the functional divergence of these denitrifying bacteria and speculated that the genetic interactions within anammox communities through horizontal gene transfer may be one of the reasons for their functional divergence.

Towards a better understanding of antimicrobial resistance dissemination: what can be learnt from studying model conjugative plasmids?

Bacteria can evolve rapidly by acquiring new traits such as virulence, metabolic properties, and most importantly, antimicrobial resistance, through horizontal gene transfer (HGT). Multidrug resistance in bacteria, especially in Gram-negative organisms, has become a global public health threat often through the spread of mobile genetic elements. Conjugation represents a major form of HGT and involves the transfer of DNA from a donor bacterium to a recipient by direct contact. Conjugative plasmids, a major vehicle for the dissemination of antimicrobial resistance, are selfish elements capable of mediating their own transmission through conjugation. To spread to and survive in a new bacterial host, conjugative plasmids have evolved mechanisms to circumvent both host defense systems and compete with co-resident plasmids. Such mechanisms have mostly been studied in model plasmids such as the F plasmid, rather than in conjugative plasmids that confer antimicrobial resistance (AMR) in important human pathogens. A better understanding of these mechanisms is crucial for predicting the flow of antimicrobial resistance-conferring conjugative plasmids among bacterial populations and guiding the rational design of strategies to halt the spread of antimicrobial resistance. Here, we review mechanisms employed by conjugative plasmids that promote their transmission and establishment in Gram-negative bacteria, by following the life cycle of conjugative plasmids.

Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions

Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.

Metagenomic analysis revealed a wide distribution of antibiotic resistance genes and biosynthesis of antibiotics in the gut of giant pandas

BACKGROUND

The gut microbiome is essential for the host's health and serves as an essential reservoir of antibiotic resistance genes (ARGs). We investigated the effects of different factors, including the dietary shifts and age, on the functional characteristics of the giant panda's gut microbiome (GPs) through shotgun metagenome sequencing. We explored the association between gut bacterial genera and ARGs within the gut based on network analysis.

RESULTS

Fecal samples (n=60) from captive juvenile, adult, and geriatric GPs were processed, and variations were identified in the gut microbiome according to different ages, the abundance of novel ARGs and the biosynthesis of antibiotics. Among 667 ARGs identified, nine from the top ten ARGs had a higher abundance in juveniles. For 102 ARGs against bacteria, a co-occurrence pattern revealed a positive association for predominant ARGs with Streptococcus. A comparative KEGG pathways analysis revealed an abundant biosynthesis of antibiotics among three different groups of GPs, where it was more significantly observed in the juvenile group. A co-occurrence pattern further revealed a positive association for the top ten ARGs, biosynthesis of antibiotics, and metabolic pathways.

CONCLUSION

Gut of GPs serve as a reservoir for novel ARGs and biosynthesis of antibiotics. Dietary changes and age may influence the gut microbiome's functional characteristics; however, it needs further studies to ascertain the study outcomes.

Deep learning for HGT insertion sites recognition

Background

Horizontal Gene Transfer (HGT) refers to the sharing of genetic materials between distant species that are not in a parent-offspring relationship. The HGT insertion sites are important to understand the HGT mechanisms. Recent studies in main agents of HGT, such as transposon and plasmid, demonstrate that insertion sites usually hold specific sequence features. This motivates us to find a method to infer HGT insertion sites according to sequence features.

Results

In this paper, we propose a deep residual network, DeepHGT, to recognize HGT insertion sites. To train DeepHGT, we extracted about 1.55 million sequence segments as training instances from 262 metagenomic samples, where the ratio between positive instances and negative instances is about 1:1. These segments are randomly partitioned into three subsets: 80% of them as the training set, 10% as the validation set, and the remaining 10% as the test set. The training loss of DeepHGT is 0.4163 and the validation loss is 0.423. On the test set, DeepHGT has achieved the area under curve (AUC) value of 0.8782. Furthermore, in order to further evaluate the generalization of DeepHGT, we constructed an independent test set containing 689,312 sequence segments from another 147 gut metagenomic samples. DeepHGT has achieved the AUC value of 0.8428, which approaches the previous test AUC value. As a comparison, the gradient boosting classifier model implemented in PyFeat achieve an AUC value of 0.694 and 0.686 on the above two test sets, respectively. Furthermore, DeepHGT could learn discriminant sequence features; for example, DeepHGT has learned a sequence pattern of palindromic subsequences as a significantly (P-value=0.0182) local feature. Hence, DeepHGT is a reliable model to recognize the HGT insertion site.

Conclusion

DeepHGT is the first deep learning model that can accurately recognize HGT insertion sites on genomes according to the sequence pattern.