The multi-kingdom microbiome catalog of the chicken gastrointestinal tract

Genomic insights into antibiotic-resistant non-typhoidal Salmonella isolates from outpatients in Minhang District in Shanghai

BACKGROUND

Salmonella enterica (S. enterica) causes tens of thousands of cases of diarrheal disease worldwide each year. However, our understanding of the genome and transmission dynamics of S. enterica in Minhang District in Shanghai, China is still insufficient. This study is aimed to better understand the population structure, antibiotic resistance patterns, and evolution dynamics of local strains.

METHODS

We sequenced 458 S. enterica strains from outpatients at Minhang District Central Hospital in Shanghai, China, from 2012 to 2021. Bioinformatics analyses on antibiotic resistance genes, virulence factors, mobile genetic elements, pathogenic islands, and phylogenetic relationships were performed.

RESULTS

Here we show that two dominant serovars are S. Enteritidis and S. Typhimurium isolated from outpatients in Minhang District in Shanghai, China. A total of 40 serovars and 53 sequence types (STs) are identified, two S. Montevideo strains isolated in 2013 belong to a newly identified ST10844, which is firstly identified in Minhang District in Shanghai, China. More than half of the isolates show resistance to fluoroquinolones and beta-lactams. Notably, 259 (56.6%) of the 458 isolates exhibit a multidrug-resistant pattern. Third-generation cephalosporin resistance gene blaCTX-M-55 is identified in 15 (3.3%) isolates, and fluoroquinolone resistance gene qnrS1 is identified in 42 (9.2%) isolates, both of which are strongly correlated with IS26. Mutations of T57S in ParC and D87Y in GyrA are observed in 149 (32.5%) and 133 (29.0%) isolates, respectively. In addition, phylogenetic analysis confirms the presence of outbreaks caused by S. Enteritidis and S. Typhimurium, respectively.

CONCLUSIONS

These results suggest local expansion and evolution in Salmonella occurred in Shanghai, China, and the underlying emergence of the undefined multidrug-resistant clone. Our findings enlarge the knowledge of local epidemics of Salmonella, especially S. Enteritidis and S. Typhimurium in Shanghai, and provide a piece of useful baseline information for future whole-genome sequencing surveillance.

The inclusion of insect meal from Hermetia illucens larvae in the diet of laying hens (Hy-line Brown) affects the caecal diversity of methanogenic archaea

The effect of the dietary inclusion of Hermetia illucens larvae meal on the diversity of the methanogenic archaea in the caecum of laying hens (Hy-line Brown) was investigated using molecular methods. A total of 27 hens, selected equally for slaughter from 162 birds which were divided equally into 3 treatment groups including control group C with a diet containing corn-soybean meal and 2 experimental groups, HI25 and HI50, in which 25% and 50% of the soybean meal protein was replaced by the protein from a Hermetia illucens larvae meal, respectively. At 40 weeks of age, the methanogenic community of caecal content of 9 hens per group was analyzed using a 16S rRNA gene clone library. A total of 108 positive clones, 35 from the control group, 44 from the HI25 group and 29 from the HI50 group, were analyzed by Sanger sequencing. Methanomicrobiales, Methanobacteriales and Methanomassiliicoccales were the main orders found in groups C and HI25. Methanomassiliicoccales was absent in the HI50 group, which was dominated by the order Methanobacteriales. At the species level, Methanobrevibacter woesei was the most prevalent species in all three groups regardless of diet. Some species were found exclusively either in the control group (Methanogenic archaeon CH1270) or in the HI25 group (Methanorbis furvi strain Ag1). Methanogenic diversity was significantly lower in the HI50 group compared to the control and HI25 groups and Methanomassiliicoccaceae archaeon DOK was completely suppressed in HI50 group. Our preliminary results indicate that ingestion of Hermetia illucens larvae meal has considerable effect on the methanogenic community, promoting the abundance of Methanobrevibacter woesei and suppressing Methanomassiliicoccaceae archaeon DOK in the caeca of laying hens.

Do we need a standardized 16S rRNA gene amplicon sequencing analysis protocol for poultry microbiota research?

Bacteria are the major component of poultry gastrointestinal tract (GIT) microbiota and play an important role in host health, nutrition, physiology regulation, intestinal development, and growth. Bacterial community profiling based on the 16S ribosomal RNA (rRNA) gene amplicon sequencing approach has become the most popular method to determine the taxonomic composition and diversity of the poultry microbiota. The 16S rRNA gene profiling involves numerous steps, including sample collection and storage, DNA isolation, 16S rRNA gene primer selection, Polymerase Chain Reaction (PCR), library preparation, sequencing, raw sequencing reads processing, taxonomic classification, α- and β-diversity calculations, and statistical analysis. However, there is currently no standardized protocol for 16S rRNA gene analysis profiling and data deposition for poultry microbiota studies. Variations in DNA storage and isolation, primer design, and library preparation are known to introduce biases, affecting community structure and microbial population analysis leading to over- or under-representation of individual bacteria within communities. Additionally, different sequencing platforms, bioinformatics pipeline, and taxonomic database selection can affect classification and determination of the microbial taxa. Moreover, detailed experimental design and DNA processing and sequencing methods are often inadequately reported in poultry 16S rRNA gene sequencing studies. Consequently, poultry microbiota results are often difficult to reproduce and compare across studies. This manuscript reviews current practices in profiling poultry microbiota using 16S rRNA gene amplicon sequencing and proposes the development of guidelines for protocol for 16S rRNA gene sequencing that spans from sample collection through data deposition to achieve more reliable data comparisons across studies and allow for comparisons and/or interpretations of poultry studies conducted worldwide.

- Invited Review - Challenges and constraints to the sustainability of poultry farming in China

China's poultry industry is characterized by large-scale production and rich breeds, presenting both opportunities and challenges. In 2023, the industry produced 10.79 billion broilers, 28.38 million tons of eggs, and 4.88 billion waterfowl. The foundation of a thriving poultry industry lies in the continuous improvement of breeds. For instance, new lines of Lueyang black-boned chickens have been developed using genomic selection breeding, with a focus on improving production performance and unlocking their high-quality genetic potential. Precision nutrition programs enhance the expression of poultry's genetic potential and improve feed utilization efficiency. The five-dimensional feed evaluation system and the comprehensive National Feed Database provide formulators with accurate nutritional parameters of feed. Additionally, the concept of "nutrition power" and the "five-ring gold standard" enable researchers to analyze poultry's digestive physiology more effectively. Feeding management plays a crucial role in optimizing genetic potential and the effectiveness of precision nutrition. To further boost production efficiency, smart farming systems have been implemented, incorporating intelligent management of environmental factors, animal parameters, and poultry health tracking. Meanwhile, in order to improve material utilization efficiency across the entire poultry production chain and support the sustainable development of the poultry industry, it is essential to optimize and promote the application of the Poultry-Crop interaction systems. In summary, strengthening fundamental research in poultry, optimizing smart poultry farm platforms, and implementing Poultry-Crop Interacting systems will drive the sustainable development of China's poultry industry.

Deciphering antibiotic resistance genes and plasmids in pathogenic bacteria from 166 hospital effluents in Shanghai, China

Although previous studies using phenotypic or metagenomic approaches have revealed the patterns of antibiotic resistance genes (ARGs) in hospital effluents in local regions, limited information is available regarding the antibiotic resistome and plasmidome in human pathogenic bacteria in hospital effluents of megacity in China. To address this knowledge gap, we analyzed effluent samples from 166 hospitals across 13 geographical districts in Shanghai, China, using both cultivation-based approaches and metagenomics. A total of 357 strains were isolated from these samples, with the predominant species being Escherichia coli (n = 61), Aeromonas hydrophila (n = 57), Klebsiella pneumoniae (n = 48), and Aeromonas caviae (n = 42). Those identified indicator bacteria were classified into biosafety level 1 (BSL-1, 60 %) and BSL-2 (40 %). We identified 1237 ARG subtypes across 22 types, predominantly including beta-lactam, tetracycline, multidrug, polymyxin, and aminoglycoside resistance genes, using culture-enriched phenotypic metagenomics. Mobile genetic elements such as plasmids, transposons (tnpA), integrons (intI1), and insertion sequences (IS91) were abundant. We recovered 135 plasmids classified into mobilizable (n = 94) and non-mobilizable (n = 41) types. Additionally, 80 metagenome-assembled genomes (MAGs) were reconstructed from the hospital effluents for the assessment of ARG transmission risks, including genes for last-line antibiotics such as blaNDM, blaKPC, blaimiH, and mcr. This study is the first to comprehensively characterize and assess the risk of antimicrobial resistance levels and plasmidome in the hospital effluents of China's megacity, providing city-wide surveillance data and evidence to inform public health interventions.

Unlocking the Potential of Metagenomics with the PacBio High-Fidelity Sequencing Technology

Traditional methods for studying microbial communities have been limited due to difficulties in culturing and sequencing all microbial species. Recent advances in third-generation sequencing technologies, particularly PacBio's high-fidelity (HiFi) sequencing, have significantly advanced metagenomics by providing accurate long-read sequences. This review explores the role of HiFi sequencing in overcoming the limitations of previous sequencing methods, including high error rates and fragmented assemblies. We discuss the benefits and applications of HiFi sequencing across various environments, such as the human gut and soil, which provides broader context for further exploration. Key studies are discussed to highlight HiFi sequencing's ability to recover complete and coherent microbial genomes from complex microbiomes, showcasing its superior accuracy and continuity compared to other sequencing technologies. Additionally, we explore the potential applications of HiFi sequencing in quantitative microbial analysis, as well as the detection of single nucleotide variations (SNVs) and structural variations (SVs). PacBio HiFi sequencing is establishing a new benchmark in metagenomics, with the potential to significantly enhance our understanding of microbial ecology and drive forward advancements in both environmental and clinical applications.

Metagenomics Analysis Reveals the Composition and Functional Differences of Fecal Microbiota in Wild, Farm, and Released Chinese Three-Keeled Pond Turtles (Mauremys reevesii)

The intestine of living organisms harbors different microbiota associated with the biological functioning and health of the host and influences the process of ecological adaptation. Here, we studied the intestinal microbiota's composition and functional differences using 16S rRNA and metagenomic analysis in the wild, farm, and released Chinese three-keeled pond turtle (Mauremys reevesii). At the phylum level, Bacteroidota dominated, followed by Firmicutes, Fusobacteriota, and Actinobacteriota in the wild group, but Chloroflexi was more abundant in the farm and released groups. Moreover, Chryseobacterium, Acinetobacter, Comamonas, Sphingobacterium, and Rhodobacter were abundant in the released and farm cohorts, respectively. Cetobacterium, Paraclostridium, Lysobacter, and Leucobacter showed an abundance in the wild group. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database revealed that the relative abundance of most pathways was significantly higher in the wild turtles (carbohydrate metabolism, lipid metabolism, metabolism of cofactors, and vitamins). The comprehensive antibiotic resistance database (CARD) showed that the antibiotic resistance gene (ARG) subtype macB was the most abundant in the farm turtle group, while tetA was higher in the wild turtles, and srpYmcr was higher in the released group. Our findings shed light on the association between the intestinal microbiota of M. reevesii and its habitats and could be useful for tracking habitats to protect and conserve this endangered species.