Exploring Pathogen Presence Prediction in Pastured Poultry Farms through Transformer-Based Models and Attention Mechanism Explainability.

In this study, we explore how transformer models, which are known for their attention mechanisms, can improve pathogen prediction in pastured poultry farming. By combining farm management practices with microbiome data, our model outperforms traditional prediction methods in terms of the F1 score-an evaluation metric for model performance-thus fulfilling an essential need in predictive microbiology. Additionally, the emphasis is on making our model's predictions explainable.

Characterization of an Arginine Decarboxylase from by Ultrahigh-Performance Liquid Chromatography-Tandem Mass Spectrometry.

Polyamines are polycations derived from amino acids that play an important role in proliferation and growth in almost all living cells. In (the pneumococcus), modulation of polyamine metabolism not only plays an important regulatory role in central metabolism, but also impacts virulence factors such as the capsule and stress responses that affect survival in the host. However, functional annotation of enzymes from the polyamine biosynthesis pathways in the pneumococcus is based predominantly on computational prediction.

Impact of Difluoromethylornithine and AMXT 1501 on Gene Expression and Capsule Regulation in .

(Spn), a Gram-positive bacterium, poses a significant threat to human health, causing mild respiratory infections to severe invasive conditions. Despite the availability of vaccines, challenges persist due to serotype replacement and antibiotic resistance, emphasizing the need for alternative therapeutic strategies. This study explores the intriguing role of polyamines, ubiquitous, small organic cations, in modulating virulence factors, especially the capsule, a crucial determinant of Spn's pathogenicity.

Predicting MIC and Deciphering Genomic Determinants of Antibiotic Resistance and Susceptibility.

spp., a leading cause of foodborne illness, is a formidable global menace due to escalating antimicrobial resistance (AMR). The evaluation of minimum inhibitory concentration (MIC) for antimicrobials is critical for characterizing AMR.

Predicting foodborne pathogens and probiotics taxa within poultry-related microbiomes using a machine learning approach.

Background: Microbiomes that can serve as an indicator of gut, intestinal, and general health of humans and animals are largely influenced by food consumed and contaminant bioagents. Microbiome studies usually focus on estimating the alpha (within sample) and beta (similarity/dissimilarity among samples) diversities. This study took a combinatorial approach and applied machine learning to microbiome data to predict the presence of disease-causing pathogens and their association with known/potential probiotic taxa.

An ensemble learning approach to identify pastured poultry farm practice variables and soil constituents that promote prevalence.

Animal sourced foods including contaminated poultry meat and eggs contribute to human non-typhoidal salmonellosis, a foodborne zoonosis. Prevalence of in pastured poultry production systems can lead to contamination of the final product. Identification of farm practices that affect prevalence is critical for implementing control measures to ensure the safety of these products.

Negatively Affects Bovine Herpesvirus Type 1.1 Replication Capacity In Vitro.

Bovine Respiratory Disease (BRD) is a multifactorial condition affecting cattle worldwide resulting in high rates of morbidity and mortality. The disease can be triggered by Bovine Herpesvirus-1 (BoHV-1) infection, stress, and the subsequent proliferation and lung colonization by commensal bacteria such as , ultimately inducing severe pneumonic inflammation. Due to its polymicrobial nature, the study of BRD microbes requires co-infection models.

Using Activity-Based Proteomics for the Quantification of Deubiquitinases in Animal Tissue.

Ubiquitination is a post-translational modification, that regulates essential cellular functions, and the enzymes that control the removal of this modification, deubiquitinases (DUBs), have been well described for the model organisms. However, the information about DUBs is still largely lacking for the non-model organisms, such as agriculturally relevant animals. To understand the expression of these enzymes in animal tissues, we have used chemical proteomics which can be used to identify biologically active DUBs present in tissues based on their reactivity with the activity-based probes (ABPs).

Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain.

Bovine respiratory disease (BRD), the leading disease complex in beef cattle production systems, remains highly elusive regarding diagnostics and disease prediction. Previous research has employed cellular and molecular techniques to describe hematological and gene expression variation that coincides with BRD development. Here, we utilized weighted gene co-expression network analysis (WGCNA) to leverage total gene expression patterns from cattle at arrival and generate hematological and clinical trait associations to describe mechanisms that may predict BRD development.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey.

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread.

Preharvest Environmental and Management Drivers of Multidrug Resistance in Major Bacterial Zoonotic Pathogens in Pastured Poultry Flocks.

Due to nutritional benefits and perceived humane ways of treating the animals, the demand for antibiotic-free pastured poultry chicken has continued to be steadily rise. Despite the non-usage of antibiotics in pastured poultry broiler production, antibiotic resistance (AR) is reported in zoonotic poultry pathogens. However, factors that drive multidrug resistance (MDR) in pastured poultry are not well understood.

Difluoromethylornithine (DFMO) and AMXT 1501 inhibit capsule biosynthesis in pneumococci.

Polyamines are small cationic molecules that have been linked to various cellular processes including replication, translation, stress response and recently, capsule regulation in Streptococcus pneumoniae (Spn, pneumococcus). Pneumococcal-associated diseases such as pneumonia, meningitis, and sepsis are some of the leading causes of death worldwide and capsule remains the principal virulence factor of this versatile pathogen. α-Difluoromethyl-ornithine (DFMO) is an irreversible inhibitor of the polyamine biosynthesis pathway catalyzed by ornithine decarboxylase and has a long history in modulating cell growth, polyamine levels, and disease outcomes in eukaryotic systems.

Use of nCounter mRNA profiling to identify at-arrival gene expression patterns for predicting bovine respiratory disease in beef cattle.

Background: Transcriptomics has identified at-arrival differentially expressed genes associated with bovine respiratory disease (BRD) development; however, their use as prediction molecules necessitates further evaluation. Therefore, we aimed to selectively analyze and corroborate at-arrival mRNA expression from multiple independent populations of beef cattle. In a nested case-control study, we evaluated the expression of 56 mRNA molecules from at-arrival blood samples of 234 cattle across seven populations via NanoString nCounter gene expression profiling.

Multipopulational transcriptome analysis of post-weaned beef cattle at arrival further validates candidate biomarkers for predicting clinical bovine respiratory disease.

Bovine respiratory disease (BRD) remains the leading infectious disease in post-weaned beef cattle. The objective of this investigation was to contrast the at-arrival blood transcriptomes from cattle derived from two distinct populations that developed BRD in the 28 days following arrival versus cattle that did not. Forty-eight blood samples from two populations were selected for mRNA sequencing based on even distribution of development (n = 24) or lack of (n = 24) clinical BRD within 28 days following arrival; cattle which developed BRD were further stratified into BRD severity cohorts based on frequency of antimicrobial treatment: treated once (treated_1) or treated twice or more and/or died (treated_2+).

No-boundary thinking: a viable solution to ethical data-driven AI in precision medicine.

Today Artificial Intelligence (AI) supports difficult decisions about policy, health, and our personal lives. The AI algorithms we develop and deploy to make sense of information, are informed by data, and based on models that capture and use pertinent details of the population or phenomenon being analyzed. For any application area, more importantly in precision medicine which directly impacts human lives, the data upon which algorithms are run must be procured, cleaned, and organized well to assure reliable and interpretable results, and to assure that they do not perpetrate or amplify human prejudices.

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology.

Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understanding of host response related to BRD pathophysiology. Supervised machine learning (ML) approaches present one such method for analyzing new and previously published transcriptome data to identify novel disease-associated genes and mechanisms.

The Effect of Impaired Polyamine Transport on Pneumococcal Transcriptome.

Infections due to , a commensal in the nasopharynx, still claim a significant number of lives worldwide. Genome plasticity, antibiotic resistance, and limited serotype coverage of the available polysaccharide-based conjugate vaccines confounds therapeutic interventions to limit the spread of this pathogen. Pathogenic mechanisms that allow successful adaption and persistence in the host could be potential innovative therapeutic targets.

Identification of active deubiquitinases in the chicken tissues.

The existing protein annotation in chicken is mostly limited to computational predictions based on orthology to other proteins, which often leads to a significant underestimation of the function of these proteins. Genome-scale experimental annotation can provide insight into the actual enzymatic activities of chicken proteins. Amongst post-translational modifications, ubiquitination is of interest as anomalies in ubiquitination are implicated in such diseases as inflammatory disorders, infectious diseases, or malignancies.

Comprehensive at-arrival transcriptomic analysis of post-weaned beef cattle uncovers type I interferon and antiviral mechanisms associated with bovine respiratory disease mortality.

Background: Despite decades of extensive research, bovine respiratory disease (BRD) remains the most devastating disease in beef cattle production. Establishing a clinical diagnosis often relies upon visual detection of non-specific signs, leading to low diagnostic accuracy. Thus, post-weaned beef cattle are often metaphylactically administered antimicrobials at facility arrival, which poses concerns regarding antimicrobial stewardship and resistance.

Arginine Decarboxylase Is Essential for Pneumococcal Stress Responses.

Polyamines such as putrescine, cadaverine, and spermidine are small cationic molecules that play significant roles in cellular processes, including bacterial stress responses and host-pathogen interactions. is an opportunistic human pathogen, which causes several diseases that account for significant morbidity and mortality worldwide. As it transits through different host niches, is exposed to and must adapt to different types of stress in the host microenvironment.

The expansive effects of polyamines on the metabolism and virulence of Streptococcus pneumoniae.

Polyamines are common intracellular metabolites of nearly all cells, and their conservation across a vast diversity of cells suggests critical roles for these compounds in cellular physiology. Most intracellular polyamines are associated with RNA and, subsequently, polyamines have significant effects on transcription and translation. Putrescine and spermidine are the most common polyamines in bacteria.

SP_0916 Is an Arginine Decarboxylase That Catalyzes the Synthesis of Agmatine, Which Is Critical for Capsule Biosynthesis in .

The global burden of invasive pneumococcal diseases, including pneumonia and sepsis, caused by , a Gram-positive bacterial pathogen, remains a major global health risk. The success of pneumococcus as a pathogen can be attributed to its ability to regulate the synthesis of capsular polysaccharide (CPS) during invasive disease. We previously reported that deletion of a putative lysine decarboxylase (LDC; ΔSP_0916) in pneumococcal serotype 4 (TIGR4) results in reduced CPS.

metal homeostasis alters cellular metabolism.

Streptococcus pneumoniae colonizes the human nasopharyngeal mucosa and is a leading cause of community-acquired pneumonia, acute otitis media, and bacterial meningitis. Metal ion homeostasis is vital to the survival of this pathogen across diverse biological sites and contributes significantly to colonization and invasive disease. Microarray and qRT-PCR analysis revealed an upregulation of an uncharacterized operon (SP1433-1438) in pneumococci subjected to metal-chelation by N,N,N',N'-tetrakis-(2-pyridylmethyl)ethylenediamine (TPEN).