The rumen is the largest of the four chambers of the “stomach” in ruminant animals, which harbors an incredibly dense, diverse, and dynamic microbial community crucial for feedstuff degradation, animal health, and production. The primary objective of this article is to enhance knowledge and comprehension of rumen microbiology by providing an introductory-level overview of the field of rumen microbiology. Ruminants possess a distinctive digestive system optimized for the microbial breakdown of complex plant materials. The ruminant ”stomach” consists of four chambers (e.g., reticulum, rumen, omasum, and abomasum), which is home to a microbial population that degrades feedstuffs consumed by ruminant animals. Dr. Robert Hungate and Dr. Marvin Bryant’s groundbreaking research in the 1960s laid the foundation for understanding the function of the ruminal microbial ecosystem. Recent advancements (e.g., next-generation sequencing) have provided the field with deeper insight into populations, boosting our understanding of how the microbial population of the rumen functions in a variety of conditions. The ruminal microbial ecosystem is comprised of bacteria, along with archaea, protozoa, bacteriophage, and fungi, each contributing to the symbiotic relationship between the microbial ecosystem and the host animal that is essential for optimal animal health and efficient animal production. Traditional anaerobic growth techniques have facilitated the study of individual anaerobic bacteria but have been limited by dependence on growth in laboratory conditions. The development of 16S rRNA sequencing allows the identification of microbial populations that cannot be grown and allows an unbiased view of microbial diversity. Diet shapes the rumen microbial population composition, influencing animal production metrics such as feed efficiency, methane emissions, and immunological functions. Feed additives (e.g., essential oils, eubiotics) hold promise by manipulating and unraveling the microbial biochemical potential for improving animal health, feed efficiency, environmental impacts, and overall production sustainability. Future research impacts include the development of probiotics, prebiotics, and genetic strategies for optimizing the rumen microbiome’s multifaceted impacts.

The holobiont concept has emerged as an attempt to recognize and describe the myriad interactions and physiological signatures inherent to a host organism, as affected by the microbial communities that colonize and co-inhabit the environment within which the host resides. The field acknowledges and draws upon principles from evolution, ecology, genetics, and biology, and in many respects has been pushed by the advent of high throughput DNA sequencing and, to a lesser extent, other omics-based technologies. Despite the explosion in data generation and analyses, much of our current understanding of the human and ruminant holobiont is based on compositional forms of data and thereby, restricted to describing host phenotypes via associative or correlative studies. So, where to from here? We will discuss some past findings arising from ruminant and human gut microbiota research and seek to evaluate the rationale, progress, and opportunities that might arise from the holobiont approach to the ruminant and human host. In particular, we will consider what is a "good" or "bad" host gastrointestinal microbiome in different scenarios, as well as potential avenues to sustain or alter the holobiont. Although the holobiont approach might improve food quality, food security, and animal health, these benefits will most likely be achieved via a judicious and pragmatic compromise in data generation, both in terms of its scale as well as its generation, in context with the forgotten knowledge of ruminant and human physiology.

Escherichia coli is a common gastrointestinal bacteria that has a vast genetic, physiologic, and biochemical diversity in E. coli, which allows this organism to thrive in many environments. But E. coli contains several pathogenic groups (e.g., pathotypes) which can cause disease and morbidity in poultry, reduce poultry producers profitability, and can impact the health and safety of human consumers of poultry meat products. As the use of antimicrobials as growth promoters has become increasingly restricted, alternatives to antimicrobials (ATA) have become a higher priority. The use of probiotics, prebiotics, postbiotics, bacteriophage, and organic acids have the potential to alter the gastrointestinal microbial population and to reduce pathogenic groups of E. coli. Thus strategies that can reduce these important pathogens from poultry are critical to ensuring the efficient production of poultry meat, but also the safety of these important sources of protein for humans.

Historically, methods to detect subclinical mastitis have been used to aid treatment decisions. The limitations of these tests have led to the exploration of the use of differential somatic cell count (DSCC). The objective of this study was to evaluate the relationship between DSCC and antibiotic success in subclinically infected cows. Cows were pre-screened to confirm an SCC ≥ 200,000 cells/mL and a positive bacterial culture. At enrollment, aseptic quarter milk samples were collected for culturing and evaluated using SCC, DSCC, the California Mastitis Test (CMT), and electrical conductivity. Enrolled quarters were treated with an intramammary antibiotic and resampled 7-, 14-, 28-, and 35-days post-treatment and retrospectively classified as “Cured” or failed to cure (Failed) based on a bacteriological cure. The overall cure rate was 51.5%. Pre-treatment SCC, total leukocyte count (TLC), neutrophils, and CMT were lower in Cured quarters compared to Failed. Meanwhile, macrophage percentage was greater in Cured quarters compared to Failed. No difference was found between lymphocyte percentage and conductivity. When evaluating the use of multiple threshold optimizations to predict cure outcome, TLC tended to have the highest ranking for the metric of interest; however, SCC tended to numerically perform as well in sensitivity and specificity outside of the optimized parameter.

Small ruminants, such as newborn lambs, rely on timely colostrum intake to acquire passive immunity through the absorption of immunoglobulin (Ig). Evaluating Ig transfer is important for ensuring lamb health and survival. However, current methods such as enzyme-linked immunosorbent assay (ELISA) and radial immunodiffusion (RID) are widely used but remain costly and require specialized facilities. The immunocrit assay has been proposed as a lower-cost alternative for evaluating serum Ig concentrations. This study aimed to evaluate the immunocrit method in lambs by comparing it with ELISA, RID, and total serum protein. Serum was collected from 135 Katahdin-Easycare lambs 24–36 h after birth. Samples were analyzed using sheep immunoglobulin G ELISA, Sheep immunoglobulin G RID, serum protein, and the immunocrit method. Pearson’s correlation was used to assess linear relationships between the methods, and Receiver Operating Characteristics (ROC) analysis was used to evaluate test accuracy, with RID as the gold standard (15 mg/mL cutoff). The immunocrit showed a high correlation with RID (r = 0.870), moderate correlation with serum protein (r = 0.725), and good correlation with ELISA (r = 0.607). The ROC analysis showed that the immunocrit had a sensitivity of 100% at a cutoff of 4.34%. These results indicate that the immunocrit method provides comparable accuracy to RID and serum protein, and could serve as a reliable, practical, and inexpensive tool for on-farm evaluation of passive transfer in Katahdin-Easycare crossbred lambs between 24 and 36 h after birth.