The initial development of intestinal microbiota in poultry plays an important role in production performance, overall health and resistance against microbial infections. Multiplexed sequencing of 16S ribosomal RNA gene amplicons is often used in studies, such as feed intervention or antimicrobial drug trials, to determine corresponding effects on the composition of intestinal microbiota. However, considerable variation of intestinal microbiota composition has been observed both within and across studies. Such variation may in part be attributed to technical factors, such as sampling procedures, sample storage, DNA extraction, the choice of PCR primers and corresponding region to be sequenced, and the sequencing platforms used. Furthermore, part of this variation in microbiota composition may also be explained by different host characteristics and environmental factors. To facilitate the improvement of design, reproducibility and interpretation of poultry microbiota studies, we have reviewed the literature on confounding factors influencing the observed intestinal microbiota in chickens. First, it has been identified that host-related factors, such as age, sex, and breed, have a large effect on intestinal microbiota. The diversity of chicken intestinal microbiota tends to increase most during the first weeks of life, and corresponding colonization patterns seem to differ between layer- and meat-type chickens. Second, it has been found that environmental factors, such as biosecurity level, housing, litter, feed access and climate also have an effect on the composition of the intestinal microbiota. As microbiota studies have to deal with many of these unknown or hidden host and environmental variables, the choice of study designs can have a great impact on study outcomes and interpretation of the data. Providing details on a broad range of host and environmental factors in articles and sequence data repositories is highly recommended. This creates opportunities to combine data from different studies for meta-analysis, which will facilitate scientific breakthroughs toward nutritional and husbandry associated strategies to improve animal health and performance.

The intestinal microbiota is shaped by many interactions between microorganisms, host, diet, and the environment. Exposure to microorganisms present in the environment, and exchange of microorganisms between hosts sharing the same environment, can influence intestinal microbiota of individuals, but how this affects microbiota studies is poorly understood. We investigated the effects of experimental housing circumstances on intestinal microbiota composition in broiler chickens, and how these effects may influence the capacity to determine diet related effects in a nutrition experiment. A cross-sectional experiment was conducted simultaneously in a feed research facility with mesh panels between pens (Housing condition 1, H1), in an extensively cleaned stable with floor pens with solid wooden panels (H2), and in isolators (H3). In H1 and H2 different distances between pens were created to assess gut microbiota exchange between pens. Feed with and without a blend of medium-chain fatty acids (MCFA) was used to create differences in cecal microbiota between pens or isolators within the same housing condition. Male one-day-old Ross broiler chickens (n = 370) were randomly distributed across H1, H2, and H3. After 35 days cecal microbiota composition was assessed by 16S ribosomal RNA gene amplicon sequencing. Metabolic functioning of cecal content was assessed based on high-performance liquid chromatography. Microbial alpha diversity was not affected in broilers fed +MCFA in H1 but was increased in H2 and H3. Based on weighted UniFrac distances, the nutritional intervention explained 10%, whereas housing condition explained 28% of cecal microbiota variation between all broilers. The effect size of the nutritional intervention varied within housing conditions between 11, 27, and 13% for H1, H2, and H3. Furthermore, performance and metabolic output were significantly different between housing conditions. The distance between pens within H1 and H2 did not influence the percentage of shared genera or operational taxonomic units (OTUs). The cecal microbiota of broilers was modifiable by a nutritional intervention, but the housing condition affected microbiota composition and functionality stronger than the diet intervention. Consequently, for interpretation of intestinal microbiota studies in poultry it is essential to be aware of the potentially large impact of housing conditions on the obtained results.

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.

Drinking water distribution systems (DWDSs) represent an ideal environment for biofilm formation, which can harbor pathogenic and antimicrobial-resistant bacteria. This study aimed to assess longitudinally the microbial community composition and antimicrobial resistance (AMR), as determined by 16S rRNA NGS and qPCR, respectively, in drinking water (DW) and biofilm from DWDSs, as well as faeces, of free-range organic broiler farms. The role of DWDSs in AMR gene (ARG) dissemination within the farm environment and transmission to animals, was also assessed. DW and biofilm microbial communities differed from those of faecal samples. Moreover, potentially pathogenic and opportunistic bacteria (e.g., Staphylococcaceae) were identified in water and biofilms. High prevalence and abundance of ARGs conferring resistance to carbapenems (i.e., bla_NDM), 3rd and 4th generation cephalosporins (i.e., bla_CMY-2), (fluoro)quinolones (i.e., qnrS), and polymyxins (i.e., mcr-3 and mcr-5) were detected in DW, biofilm, and faecal samples, which is of concern for both animal and human health. Although other factors (e.g., feed, pests, and wildlife) may contribute to the dissemination of AMR in free-range organic poultry farms, this study indicates that DWDSs can also play a role.

In the short life of broiler chickens, their intestinal microbiota undergoes many changes. To study underlying biological mechanisms and factors that influence the intestinal microbiota development, longitudinal data from flocks and individual birds is needed. However, post-mortem collection of samples hampers longitudinal data collection. In this study, invasively collected cecal and ileal content, cloacal swabs collected from the same bird, and boot sock samples and cecal droppings from the litter of the broilers’ poultry house, were collected on days 0, 2, 7, 14 and 35 post-hatch. The different sample types were evaluated on their applicability and reliability to characterize the broiler intestinal microbiota. The microbiota of 247 samples was assessed by 16S ribosomal RNA gene amplicon sequencing. Analyses of α and β measures showed a similar development of microbiota composition of cecal droppings compared to cecal content. Furthermore, the composition of cecal content samples was comparable to that of the boot socks until day 14 post-hatch. This study shows that the value of non-invasive sample types varies at different ages and depends on the goal of the microbiota characterization. Specifically, cecal droppings and boot socks may be useful alternatives for cecal samples to determine intestinal microbiota composition longitudinally.