Identification of Potential Tryptase Inhibitors from FDA-Approved Drugs Using Machine Learning, Molecular Docking, and Experimental Validation.

This study explores the innovative use of machine learning (ML) to identify novel tryptase inhibitors from a library of FDA-approved drugs, with subsequent confirmation via molecular docking and experimental validation. Tryptase, a significant mediator in inflammatory and allergic responses, presents a therapeutic target for various inflammatory diseases. However, the development of effective tryptase inhibitors has been challenging due to the enzyme's complex activation and regulation mechanisms. Utilizing a machine learning model, we screened an extensive FDA-approved drug library to identify potential tryptase inhibitors. The predicted compounds were then subjected to molecular docking to assess their binding affinity and conformation within the tryptase active site. Experimental validation was performed using RBL-2H3 cells, a rat basophilic leukemia cell line, where the efficacy of these compounds was evaluated based on their ability to inhibit tryptase activity and suppress ß-hexosaminidase activity and histamine release. Our results demonstrated that several FDA-approved drugs, including landiolol, laninamivir, and cidofovir, significantly inhibited tryptase activity. Their efficacy was comparable to that of the FDA-approved mast cell stabilizer nedocromil and the investigational agent APC-366. These findings not only underscore the potential of ML in accelerating drug repurposing but also highlight the feasibility of this approach in identifying effective tryptase inhibitors. This research contributes to the field of drug discovery, offering a novel pathway to expedite the development of therapeutics for tryptase-related pathologies.

Anelosimuseximius bioinspired ZnO nano cobwebs for environmental remediation of drugs and endocrine disruptors from water.

The pollution of wastewater with pharmaceuticals and endocrine-disrupting chemicals (EDCs) in populated areas poses a growing threat to humans and ecosystems. To address this serious problem, various one-dimensional (1D) hierarchical ZnO-based nanostructures inspired by Anelosimus eximius cobwebs were developed and successfully grown on a glass substrate through simple hydrothermal synthesis. The nanorods (nr) obtained during primary growth were chemically etched with KOH (ZnOnr-KOH), followed by the secondary growth of nano cobweb-like (ncw) structures using polyethyleneimine (ZnOnr/ncw). These structures were further decorated by the photoreduction of Ag nanoparticles (ZnOnr/ncw/Ag). The feasibility of ZnO-based 1D nanostructures to remove pollutants was demonstrated by degrading commonly prescribed pharmaceutical drugs (diclofenac and carbamazepine) in a miniature cuvette reactor. The photocatalytic activities for drug degradation generally decreased in the order ZnOnr/ncw/Ag > ZnOnr/ncw > ZnOnr-KOH. Additionally, the suitability of the samples for scaling up and practical application was demonstrated by photocatalytic degradation of the hormone estriol (E3) in a flow-through photoreactor. The photocatalytic degradation efficiency of E3 followed the same trend observed for drug degradation, with the complete elimination of the endocrine disruptor achieved by the best-performing ZnOnr/ncw/Ag within 4 h, due to optimized charge transfer and separation at the heterostructure interface.

Photocatalytically active layered double hydroxide-PVDF composite membranes for effective remediation of dyes contaminated water.

In this work, polyvinylidene fluoride (PVDF) intercalated CuFe layered double hydroxides (LDH) membranes were fabricated and investigated for UV-LED/persulfate degradation of methylene blue (MB), crystal violet (CV), methyl orange (MO), and Eriochrome black T (EBT) dyes from water. The PVDF-CuFe membrane exhibited improved heterogeneity, surface functionality (CuO, Fe-O, Cu-O-Fe), surface roughness, and hydrophilicity. The process parameters were optimized by response surface methodology, and maximum MB removal (100%) was achieved within 45.22-178.5 min at MB concentration (29.45-101.93 mg/L), PP concentration (0.5-2.41 g/L) and catalyst dosage (1.84-1.95 g/L). The degradation kinetics was well described by a pseudo-first-order model (R2 = 0.982) and fast reaction rate (0.029-0.089/min). The MB dye degradation mechanism is associated with HO·/SO4•- reactive species generated by Fe3+/Fe2+ or Cu2+/Cu+ in PVDF-CuFe membrane and PP dissociation. The PVDF-CuFe membrane demonstrated excellent recyclability performance with a 12% reduction after five consecutive cycles. The catalytic membrane showed excellent photocatalytic degradation of crystal violet (100%), methyl orange (79%), and Eriochrome black T (60%). The results showed that UV-LED/persulfate-assisted PVDF-CuFe membranes can be used as a recyclable catalyst for the effective degradation of dye-contaminated water streams.

Finite element modeling of stress distribution and safety factors in a Ti-27Nb alloy hip implant under real-world physiological loading scenarios.

Total hip arthroplasty (THA) is one of the most successful orthopaedic interventions globally, with over 450,000 procedures annually in the U.S. alone. However, issues like aseptic loosening, dislocation, infection and stress shielding persist, necessitating complex, costly revision surgeries. This highlights the need for continued biomaterials innovation to enhance primary implant integrity and longevity. Implant materials play a pivotal role in determining long-term outcomes, with titanium alloys being the prominent choice. However, emerging evidence indicates scope for optimized materials. The nickel-free ß titanium alloy Ti-27Nb shows promise with excellent biocompatibility and mechanical properties. Using finite element analysis (FEA), this study investigated the biomechanical performance and safety factors of a hip bone implant made of nickel-free titanium alloy (Ti-27Nb) under actual loading during routine day life activities for different body weights. The FEA modelled physiological loads during walking, jogging, stair ascent/descent, knee bend, standing up, sitting down and cycling for 75 kg and 100 kg body weights. Comparative analyses were conducted between untreated versus 816-hour simulated body fluid (SBF) treated implant conditions to determine in vivo degradation effects. The FEA predicted elevated von Mises stresses in the implant neck for all activities, especially stair climbing, due to its smaller cross-section. Stresses increased substantially with a higher 100 kg body weight compared to 75 kg, implying risks for heavier patients. Safety factors were reduced by up to 58% between body weights, although remaining above the desired minimum value of 1. Negligible variations were observed between untreated and SBF-treated responses, attributed to Ti-27Nb's excellent biocorrosion resistance. This comprehensive FEA provided clinically relevant insights into the biomechanical behaviour and integrity of the Ti-27Nb hip implant under complex loading scenarios. The results can guide shape and material optimization to improve robustness against repetitive stresses over long-term use. Identifying damage accumulation and failure risks is crucial for hip implants encountering real-world variable conditions. The negligible SBF effects validate Ti-27Nb's resistance to physiological degradation. Overall, the study significantly advances understanding of Ti-27Nb's suitability for reliable, durable hip arthroplasties with low revision rates.

Therapeutic Implication of miRNAs as an Active Regulatory Player in the Management of Pain: A Review.

Chronic pain is frequently associated with neuropathy, inflammation, or the malfunctioning of nerves. Chronic pain is associated with a significant burden of morbidity due to opioid use, associated with addiction and tolerance, and disability. MicroRNAs (miRs) are emerging therapeutic targets to treat chronic pain through the regulation of genes associated with inflammation, neuronal excitability, survival, or de-differentiation. In this review, we discuss the possible involvement of miRs in pain-related molecular pathways. miRs are known to regulate high-conviction pain genes, supporting their potential as therapeutic targets.

Intrastromal Corneal Ring Implants Associated Bacterial Infections.

PURPOSE: This study examines the incidence of infection and resistance associated with Intracorneal Ring Segment (ICRS) implantation, a common outpatient surgical treatment for correcting refractive errors and corneal ectatic diseases. Although ICRS procedures are typically safe and reversible, there is a low but notable risk of microbial infections, which require prompt and sometimes invasive treatment. METHODS: Three electronic databases, PubMed, Web of Science (WoS), and Scopus, were utilised to search for literature according to PRISMA guidelines to identify infections related to the implantation of ICRS in the cornea between January 2000 and December 2022. RESULTS: Gram-positive organisms were involved in 86% of cases: 35.7% S. aureus, 25% coagulase-negative staphylococci species, 17.8% streptococci and 7.1% Nocardia species. Less commonly recorded were Gram-negative bacteria (14%), with Pseudomonas aeruginosa (circa 10%) and Klebsiella pneumonia (4%) being the most common Gram-negative bacteria. In rare cases, fungi have also been reported. ICRS-related bacterial infections can be categorised into early or late onset. Early onset infection typically manifests within the first few weeks after implantation and is often associated with contamination during surgery, unhygienic practices, or inadequate sterilisation techniques. On the other hand, late-onset infection may develop months or even years after the initial procedures and may be associated with persistent bacterial colonisation, secondary infections, or prolonged use of prophylactic antibiotics. S aureus is encountered in both early and late-onset infections, while Nocardia species and K. pneumoniae have generally been reported to occur in late-onset infections. In addition, vision recovery from S. aureus infections tends to be poor compared to other bacterial infections. CONCLUSION: S. aureus is a predominant pathogen that often requires surgical intervention with poor outcomes. Early infections result from incision gaps and ring segment rubbing, while late infections are linked to prolonged antibiotic use. Further research is needed on novel antimicrobial ICRS to procure the vision.

Molecular Role of Protein Phosphatases in Alzheimer's and Other Neurodegenerative Diseases.

Alzheimer's disease (AD) is distinguished by the gradual loss of cognitive function, which is associated with neuronal loss and death. Accumulating evidence supports that protein phosphatases (PPs; PP1, PP2A, PP2B, PP4, PP5, PP6, and PP7) are directly linked with amyloid beta (Aß) as well as the formation of the neurofibrillary tangles (NFTs) causing AD. Published data reported lower PP1 and PP2A activity in both gray and white matters in AD brains than in the controls, which clearly shows that dysfunctional phosphatases play a significant role in AD. Moreover, PP2A is also a major causing factor of AD through the deregulation of the tau protein. Here, we review recent advances on the role of protein phosphatases in the pathology of AD and other neurodegenerative diseases. A better understanding of this problem may lead to the development of phosphatase-targeted therapies for neurodegenerative disorders in the near future.

Discovery of Novel Aldose Reductase Inhibitors via the Integration of Ligand-Based and Structure-Based Virtual Screening with Experimental Validation.

Aldose reductase plays a central role in diabetes mellitus (DM) associated complications by converting glucose to sorbitol, resulting in a harmful increase of reactive oxygen species (ROS) in various tissues, such as the heart, vasculature, neurons, eyes, and kidneys. We employed a comprehensive approach, integrating both ligand- and structure-based virtual screening followed by experimental validation. Initially, candidate compounds were extracted from extensive drug and chemical libraries using the DeepChem's GraphConvMol algorithm, leveraging its capacity for robust molecular feature representation. Subsequent refinement employed molecular docking and molecular dynamics (MD) simulations, which are crucial for understanding compound-receptor interactions and dynamic behavior in a simulated physiological environment. Finally, the candidate compounds were subjected to experimental validation of their biological activity using an aldose reductase inhibitor screening kit. The comprehensive approach led to the identification of a promising compound, demonstrating significant potential as an aldose reductase inhibitor. This comprehensive approach not only yields a potential therapeutic intervention for DM-related complications but also establishes an integrated protocol for drug development, setting a new benchmark in the field.

Comparing fatal crash risk factors by age and crash type by using machine learning techniques.

This study aims to use machine learning methods to examine the causative factors of significant crashes, focusing on accident type and driver's age. In this study, a wide-ranging data set from Jeddah city is employed to look into various factors, such as whether the driver was male or female, where the vehicle was situated, the prevailing weather conditions, and the efficiency of four machine learning algorithms, specifically XGBoost, Catboost, LightGBM and RandomForest. The results show that the XGBoost Model (accuracy of 95.4%), the CatBoost model (94% accuracy), and the LightGBM model (94.9% accuracy) were superior to the random forest model with 89.1% accuracy. It is worth noting that the LightGBM had the highest accuracy of all models. This shows various subtle changes in models, illustrating the need for more analyses while assessing vehicle accidents. Machine learning is also a transforming tool in traffic safety analysis while providing vital guidelines for developing accurate traffic safety regulations.

Extensively drug-resistant Salmonella Typhi leading to relapsed urinary tract infection: A case report.

Salmonella enterica serotype Typhi (S Typhi) associated urinary tract infections are exceedingly rare, accounting for less than 1% of cases. Such infections have known to occur in immune-compromised or individuals with urogenital structural abnormalities. With the emergence of extensively drug resistant S Typhi strains in Pakistan, the management of its various unique presentations poses therapeutic challenges. We report the first documented case of a 74 years old male patient presenting with relapsed urinary tract infection secondary to extensively drug resistant S Typhi.

Meningitis and Bacteremia by Unusual Serotype of Salmonella enterica Strain: A Whole Genome Analysis.

Background: Although meningitis caused by Salmonella species is relatively rare and accounts for <1% of the confirmed cases in neonates, it is associated with case complications and fatality rates up to 50-70% when compared to other forms of Gram-negative bacilli meningitis. Objectives: We conducted an investigation into the first reported case of neonatal meningitis caused by nontyphoidal S. enterica in Jazan, a region in the southwestern part of Saudi Arabia. Methods: CSF and blood culture were collected from a female neonate patient to confirm the presence of bacterial meningitis. WGS was conducted to find out the comprehensive genomic characterization of S. enterica isolate. Results: A 3-week-old infant was admitted to a local hospital with fever, poor feeding, and hypoactivity. She was diagnosed with Salmonella meningitis and bacteremia caused by S. enterica, which was sensitive to all antimicrobials tested. WGS revealed the specific strain to be S. enterica serotype Johannesburg JZ01, belonging to ST515 and cgMLST 304742. Conclusions: We presented a genomic report of rare case of NTS meningitis in an infant who is living in a rural town in Jazan region, Saudi Arabia. Further research is required to understand the impact of host genetic factors on invasive nontyphoidal Salmonella infection.

Protecting Orthopaedic Implants from Infection: Antimicrobial Peptide Mel4 Is Non-Toxic to Bone Cells and Reduces Bacterial Colonisation When Bound to Plasma Ion-Implanted 3D-Printed PAEK Polymers.

Even with the best infection control protocols in place, the risk of a hospital-acquired infection of the surface of an implanted device remains significant. A bacterial biofilm can form and has the potential to escape the host immune system and develop resistance to conventional antibiotics, ultimately causing the implant to fail, seriously impacting patient well-being. Here, we demonstrate a 4 log reduction in the infection rate by the common pathogen S. aureus of 3D-printed polyaryl ether ketone (PAEK) polymeric surfaces by covalently binding the antimicrobial peptide Mel4 to the surface using plasma immersion ion implantation (PIII) treatment. The surfaces with added texture created by 3D-printed processes such as fused deposition-modelled polyether ether ketone (PEEK) and selective laser-sintered polyether ketone (PEK) can be equally well protected as conventionally manufactured materials. Unbound Mel4 in solution at relevant concentrations is non-cytotoxic to osteoblastic cell line Saos-2. Mel4 in combination with PIII aids Saos-2 cells to attach to the surface, increasing the adhesion by 88% compared to untreated materials without Mel4. A reduction in mineralisation on the Mel4-containing surfaces relative to surfaces without peptide was found, attributed to the acellular portion of mineral deposition.

Dimeric peptoids as antibacterial agents.

Building upon our previous study on peptoid-based antibacterials which showed good activity against Gram-positive bacteria only, herein we report the synthesis of 34 dimeric peptoid compounds and the investigation of their activity against Gram-positive and Gram-negative pathogens. The newly designed peptoids feature a di-hydrophobic moiety incorporating phenyl, bromo-phenyl, and naphthyl groups, combined with variable lengths of cationic units such as amino and guanidine groups. The study also underscores the pivotal interplay between hydrophobicity and cationicity in optimizing efficacy against specific bacteria. The bromophenyl dimeric guanidinium peptoid compound 10j showed excellent activity against S. aureus 38 and E. coli K12 with MIC of 0.8 µg mL-1 and 6.2 µg mL-1, respectively. Further investigation into the mechanism of action revealed that the antibacterial effect might be attributed to the disruption of bacterial cell membranes, as suggested by tethered bilayer lipid membranes (tBLMs) and cytoplasmic membrane permeability studies. Notably, these promising antibacterial agents exhibited negligible toxicity against mammalian red blood cells. Additionally, the study explored the potential of 12 active compounds to disrupt established biofilms of S. aureus 38. The most effective biofilm disruptors were ethyl and octyl-naphthyl guanidinium peptoids (10c and 10 k). These compounds 10c and 10 k disrupted the established biofilms of S. aureus 38 with 51 % at 4x MIC (MIC = 17.6 µg mL-1 and 11.2 µg mL-1) and 56 %-58 % at 8x MIC (MIC = 35.2 µg mL-1 and 22.4 µg mL-1) respectively. Overall, this research contributes insights into the design principles of cationic dimeric peptoids and their antibacterial activity, with implications for the development of new antibacterial compounds.

Drug Repositioning via Graph Neural Networks: Identifying Novel JAK2 Inhibitors from FDA-Approved Drugs through Molecular Docking and Biological Validation.

The increasing utilization of artificial intelligence algorithms in drug development has proven to be highly efficient and effective. One area where deep learning-based approaches have made significant contributions is in drug repositioning, enabling the identification of new therapeutic applications for existing drugs. In the present study, a trained deep-learning model was employed to screen a library of FDA-approved drugs to discover novel inhibitors targeting JAK2. To accomplish this, reference datasets containing active and decoy compounds specific to JAK2 were obtained from the DUD-E database. RDKit, a cheminformatic toolkit, was utilized to extract molecular features from the compounds. The DeepChem framework's GraphConvMol, based on graph convolutional network models, was applied to build a predictive model using the DUD-E datasets. Subsequently, the trained deep-learning model was used to predict the JAK2 inhibitory potential of FDA-approved drugs. Based on these predictions, ribociclib, topiroxostat, amodiaquine, and gefitinib were identified as potential JAK2 inhibitors. Notably, several known JAK2 inhibitors demonstrated high potential according to the prediction results, validating the reliability of our prediction model. To further validate these findings and confirm their JAK2 inhibitory activity, molecular docking experiments were conducted using tofacitinib-an FDA-approved drug for JAK2 inhibition. Experimental validation successfully confirmed our computational analysis results by demonstrating that these novel drugs exhibited comparable inhibitory activity against JAK2 compared to tofacitinib. In conclusion, our study highlights how deep learning models can significantly enhance virtual screening efforts in drug discovery by efficiently identifying potential candidates for specific targets such as JAK2. These newly discovered drugs hold promises as novel JAK2 inhibitors deserving further exploration and investigation.

A Rare Presentation of Erysipelothrix rhusiopathiae Endocarditis with Acute Heart Failure.

Erysipelothrix rhusiopathiae is an occupation-related infection that can be found in farm animals or marine life. This infection can present with a spectrum of infection ranging from local cellulitis to aortic endocarditis. Developing endocarditis is rare from this organism with only a few case reports in the literature. We presented a case of E. rhusiopathiae bacteremia that led to aortic valve endocarditis with a Gerbode defect within the mitral valve complicated with an acute exacerbation of congestive heart failure, necessitating emergent valve replacement surgery, with eventual permanent pacemaker due to complete heart block. We intend to highlight some unusual characteristics of this infection including thrombocytopenia and hyponatremia. It is important to identify this infection in early stages to prevent the late disseminating complications including endocarditis.

Genomic analysis of extensively drug resistant (XDR) Klebsiella pneumoniae high-risk clone ST14 co-harboring blaNDM and blaOXA-48 recovered from Saudi Arabia.

BACKGROUND: This study presents a comprehensive genomic analysis of NDM and OXA-48-producing Klebsiella pneumoniae in the Western region of Saudi Arabia, traversed by tens of millions of Muslims from various countries annually. This significant influx of visitors invariably leads to the spread and diversity of MDR bacteria. METHODS: Genome sequencing was performed using MiSeq system of 29 CPKP isolates that were NDM and OXA-48-positive isolated from nosocomial infections and demonstrated resistance to most antibiotics, including carbapenems. RESULTS: WGS analysis showed that 12 (41.3%) isolates co-harbored blaOXA-48,blaCTX-M-15 and blaNDM genes. Notably, 16 (55.1%) isolates were identified as high-risk clone ST14, with 50% of these isolates co-harbored blaOXA-48, blaNDM and blaCTX-M-15 genes. All ST14 isolates were identified as capsular genotype KL2 and O1/O2v1 antigen with yersiniabactin locus ypt 14 carried by ICEKp5. The two isolates were identified as ST2096/KL64 hypervirulent K. pneumoniae (hvKp) clone harboring several virulence factors, including the regulator of the mucoid phenotype rmpA2 and aerobactin (iuc-1). Interestingly, two of the hvKp ST383/KL30 isolates were resistant to all tested antimicrobials except colistin and tigecycline, and simultaneously carried numerous ESBLs and carbapenemase genes. These isolates also harbor several virulence factors such as rmpA1, rmpA2, carried on KpVP-1, and aerobactin (iuc-1). CONCLUSION: this study provides insights into the spread and prevalence of high-risk clones of CPKP in the Western region of Saudi Arabia. The ST14 high-risk clone appears to be the predominant CPKP clone in this region, posing a significant threat to public health. This study also reports the presence of two globally disseminated hypervirulent K. pneumoniae (hvKp) clones, namely ST2096 and ST383. Therefore, it is essential to improve surveillance and implement strict infection control measures in this region, which receives a substantial number of visitors to effectively monitor and reduce the spread of high-risk clones of antimicrobial-resistant bacteria, including CPKP.

Collateral sensitivity increases the efficacy of a rationally designed bacteriophage combination to control Salmonella enterica.

The ability of virulent bacteriophages to lyse bacteria influences bacterial evolution, fitness, and population structure. Knowledge of both host susceptibility and resistance factors is crucial for the successful application of bacteriophages as biological control agents in clinical therapy, food processing, and agriculture. In this study, we isolated 12 bacteriophages termed SPLA phage which infect the foodborne pathogen Salmonella enterica. To determine phage host range, a diverse collection of Enterobacteriaceae and Salmonella enterica was used and genes involved in infection by six SPLA phages were identified using Salmonella Typhimurium strain ST4/74. Candidate host receptors included lipopolysaccharide (LPS), cellulose, and BtuB. Lipopolysaccharide was identified as a susceptibility factor for phage SPLA1a and mutations in LPS biosynthesis genes spontaneously emerged during culture with S. Typhimurium. Conversely, LPS was a resistance factor for phage SPLA5b which suggested that emergence of LPS mutations in culture with SPLA1a represented collateral sensitivity to SPLA5b. We show that bacteria-phage co-culture with SPLA1a and SPLA5b was more successful in limiting the emergence of phage resistance compared to single phage co-culture. Identification of host susceptibility and resistance genes and understanding infection dynamics are critical steps in the rationale design of phage cocktails against specific bacterial pathogens.IMPORTANCEAs antibiotic resistance continues to emerge in bacterial pathogens, bacterial viruses (phage) represent a potential alternative or adjunct to antibiotics. One challenge for their implementation is the predisposition of bacteria to rapidly acquire resistance to phages. We describe a functional genomics approach to identify mechanisms of susceptibility and resistance for newly isolated phages that infect and lyse Salmonella enterica and use this information to identify phage combinations that exploit collateral sensitivity, thus increasing efficacy. Collateral sensitivity is a phenomenon where resistance to one class of antibiotics increases sensitivity to a second class of antibiotics. We report a functional genomics approach to rationally design a phage combination with a collateral sensitivity dynamic which resulted in increased efficacy. Considering such evolutionary trade-offs has the potential to manipulate the outcome of phage therapy in favor of resolving infection without selecting for escape mutants and is applicable to other virus-host interactions.

ACE2-Fc and DPP4-Fc decoy receptors against SARS-CoV-2 and MERS-CoV variants: a quick therapeutic option for current and future coronaviruses outbreaks.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and the Middle East respiratory syndrome coronavirus (MERS-CoV) are highly pathogenic human coronaviruses (CoVs). Anti-CoVs mAbs and vaccines may be effective, but the emergence of neutralization escape variants is inevitable. Angiotensin-converting enzyme 2 and dipeptidyl peptidase 4 enzyme are the getaway receptors for SARS-CoV-2 and MERS-CoV, respectively. Thus, we reformatted these receptors as Fc-fusion decoy receptors. Then, we tested them in parallel with anti-SARS-CoV (ab1-IgG) and anti-MERS-CoV (M336-IgG) mAbs against several variants using pseudovirus neutralization assay. The generated Fc-based decoy receptors exhibited a strong inhibitory effect against all pseudotyped CoVs. Results showed that although mAbs can be effective antiviral drugs, they might rapidly lose their efficacy against highly mutated viruses. We suggest that receptor traps can be engineered as Fc-fusion proteins for highly mutating viruses with known entry receptors, for a faster and effective therapeutic response even against virus harboring antibodies escape mutations.

Microbiological risk assessment and resistome analysis from shotgun metagenomics of bovine colostrum microbiome.

Colostrum is known for its nutraceutical qualities, probiotic attributes, and health benefits. The aim of this study was to profile colostrum microbiome from bovine in rural sites of a developing country. The focus was on microbiological safety assessments and antimicrobial resistance, taking into account the risks linked with the consumption of raw colostrum. Shotgun sequencing was employed to analyze microbiome in raw buffalo and cow colostrum. Alpha and beta diversity analyses revealed increased inter and intra-variability within colostrum samples' microbiome from both livestock species. The colostrum microbiome was mainly comprised of bacteria, with over 90% abundance, whereas fungi and viruses were found in minor abundance. Known probiotic species, such as Leuconostoc mesenteroides, Lactococcus lactis, Streptococcus thermophilus, and Lactobacillus paracasei, were found in the colostrum samples. A relatively higher number of pathogenic and opportunistic pathogenic bacteria were identified in colostrum from both animals, including clinically significant bacteria like Clostridium botulinum, Pseudomonas aeruginosa, Escherichia coli, and Listeria monocytogenes. Binning retrieved 11 high-quality metagenome-assembled genomes (MAGs), with three MAGs potentially representing novel species from the genera Psychrobacter and Pantoea. Notably, 175 antimicrobial resistance genes (ARGs) and variants were detected, with 55 of them common to both buffalo and cow colostrum metagenomes. These ARGs confer resistance against aminoglycoside, fluoroquinolone, tetracycline, sulfonamide, and peptide antibiotics. In conclusion, this study describes a thorough overview of microbial communities in buffalo and cow colostrum samples. It emphasizes the importance of hygienic processing and pasteurization in minimizing the potential transmission of harmful microorganisms linked to the consumption of colostrum.