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bioRxiv2024

Exploring the Educational Potential of Instagram in the New Generations: A Study on the Impact of "Adopt a Bacterium"

In 2013, the "Adopt a Bacterium" project was created, which originally proposed the use of the social network Facebook(R) as an educational tool to engage students in learning microbiology through personalized posts. However, the generational alignment dynamic presents contemporary challenges for educators. Given the relevance and success of the project in recent years, the use of an alternative social network is sought for the application of the methodology. In the present study, we describe the use of the social network Instagram as a tool to understand the impacts of the "Adopt a Bacterium" project on microbiology learning among new generations of students. To verify the effectiveness of the methodology, the following steps were taken: i) voluntary and anonymous questionnaires with an open-ended question about knowledge of the adopted bacterium were applied before the start of the project (Q1), at the end of the project (Q2), and five months after the end (Q3), to Biomedical Sciences students in the years 2020, 2021, and 2022; and ii) a project evaluation questionnaire was administered to students. The data were analyzed using thematic categorization, calculation of the richness of students discourse through the Shannon Diversity Index, and the creation of word clouds to visualize student suggestions, as well as the use of Python language tool to demonstrate citations of specific themes, comparing Facebook and Instagram as Virtual Learning Enviroments. The results revealed an improvement in student learning, as demonstrated by the increase in the frequency of content categories related to bacteriology and the richness of discourse, indicated by higher Shannon Diversity Index values in Q2 and Q3 compared to Q1. In conclusion, the results demonstrate that the methodology of the "Adopt a Bacterium" can be applied in different virtual environments, such as the social network Instagram(R) resulting in increased learning and student interest in Microbiology.

microbiology↗

bioRxiv2025

CanID-PCR: A quick and low-cost PCR tool to identify Candida species on gDNA directly extracted from positive blood bottles

Candida bloodstream infection carries a high mortality. Candida species prone to antifungal resistance (e.g. C. auris and C. glabrata) are rising, and delay in species identification might adversely affect patients outcomes. Current workflow by clinical microbiology laboratory requires [~]24 hours for Candida speciation, time to allow for growth of isolates on the agar plates for testing. We established a simple and inexpensive PCR tool, named CanID-PCR, to speciate Candida directly from positive blood bottles. We selected Candida ACT1 gene, which has an intron with varying length that enables the identification of 10 common Candida species. The tool was optimized for gDNA extracted directly from positive blood culture bottles. We showed, by testing positive blood cultures from 64 unique patients, that our tool detects the same species as the microbiology lab in 97% (62/64) of samples. The 2 samples with mismatched results were due to high similarity between Candida metapsilosis and C. parapsilosis, and failure of CanID-PCR to identify C. tropicalis in a patient with C. albicans/C. tropicalis fungemia. On the other hand, CanID-PCR identified a second species (C. fabianii) in a patient with C. parapsilosis fungemia that was missed by the microbiology laboratory. In conclusion, our inexpensive tool was accurate for rapid speciation of Candida directly from blood culture bottles, which could be valuable for clinical and/or research laboratories.

microbiology↗

bioRxiv2025

MIC*: A Framework for Interpretable Analysis of Ordinal Viability Data

Microbial survival assays frequently use ordered categorical (ordinal) scores, such as semi-quantitative viability scores across drug concentrations. While these ordinal data provide rich information about dose-response dynamics, they require appropriate statistical approaches for proper analysis. Proportional-odds (PO) ordinal regression is specifically designed for such data, modeling the ordered nature of scores while accommodating continuous variables such as concentration. However, despite its advantages, PO regression remains underutilized in microbiology because its cumulative log-odds outputs are abstract and biologically unintuitive. Consequently, researchers often resort to flawed alternatives: collapsing scores into binary outcomes (growth/no growth), treating scores as continuous values for t-tests or ANOVA, or applying nonparametric tests that ignore dose-response structure. Each approach sacrifices power or validity, risking unreliable conclusions. To allow researchers to better leverage the power of ordinal datasets, we introduce MIC*, a summary measure that translates PO regression results into biologically interpretable units. MIC* is defined as the treatment concentration where the predicted probability of "no viability" equals 0.5, and is thus conceptually related to the minimum inhibitory dose (MIC) widely used in antimicrobial research. MIC* retains the rigor of ordinal regression while providing more biologically intuitive effect size measures. The MIC* framework enables formal comparisons as absolute differences ({Delta}MIC*) or relative fold-changes ({Delta}log2MIC*), allowing for robust statistical comparisons between samples. Monte Carlo simulations demonstrate that MIC* yields robust estimates with superior power compared to conventional statistical methods, while case studies demonstrate practical utility. To ensure wide adoption, we provide a suite of open-source tools: a BLInded Scoring System (BLISS) for generating ordinal viability scores, and web-based (MICalculator) and R package (ordinalMIC) alternatives for performing complete MIC* analyses, thus reducing barriers to appropriate analysis of ordinal phenotypes in microbiology. ImportanceMicrobiologists routinely use visual scoring systems to assess cell viability for antimicrobial and stress resistance studies. However, current analysis approaches tend to be problematic, with researchers seeking simple approaches that either discard valuable information or violate important statistical assumptions. While rigorous and appropriate statistical approaches exist, they are rarely used in microbiology because they produce outputs that are non-intuitive and require specialized expertise to implement. Our MIC* framework overcomes these longstanding barriers by translating abstract outputs into an intuitive, concentration-based metric akin to the minimum inhibitory concentration (MIC) well Known to microbiologists. MIC* allows for biologically interpretable comparisons on both absolute ({Delta}MIC*) and relative ({Delta}log2MIC*) scales, allowing for facile between-sample comparisons. MIC* outperforms conventional statistical approaches, and we offer user-friendly software tools to enable broad adoption by the community.

microbiology↗

bioRxiv2019

A real-time multiplexed microbial growth intervalometer for capturing high resolution growth curves

Batch cultures are a low maintenance and routine culturing method used in anaerobic microbiology. Automated tools that measure growth curves from anaerobic microorganisms grown in traditional laboratory glassware, such as Balch-type tubes, are not commercially available. Here we present a new MicrobiAl Growth Intervalometer (MAGI) that captures microbial growth curves through photo conductivity of the medium using a diffused light pattern of specified frequency, rather than photo-attenuation of collimated light used in traditional systems, and is configured with an offset photodetector/emitter to minimize direct impingement of light from the source to improve the resolution of the solutions density. MAGI is operated by software-driven automation and offers investigators a low noise/high gain instrument with capabilities for remote visualization and data acquisition. MAGI is a low maintenance, low cost, and robust platform primarily for anaerobic cultivation and growth monitoring. We demonstrate the utility of this device by first showing that growth rates and generation times in Escherichia coli K-12 are reproducible to previously published results. We then tested MAGI to measure growth curves of an environmental organism, Intrasporangium calvum, under various media compositions. Our results demonstrate that MAGI is a versatile platform to measure growth curves in media under various redox conditions (microaerobic and anaerobic), complex mediums such as Luria-Bertani (LB) broth and minimal media, and for resolving diauxic growth curves when I. calvum is grown on a disaccharide. Lastly, we demonstrate that the device can resolve growth curves for M concentrations of resources that yield low biomass. This research advances the tools available to microbiologist aiming to monitor growth curves in a variety of disciplines, such as environmental microbiology, clinical microbiology, and food sciences.

microbiology↗

bioRxiv2019

RATIONAL DECISION ON THE USE OF ANTIBIOTICS DURING THE DRY PERIOD IN DAIRY COWS

The aim of this study was to evaluate the use of antibiotics in cows during the dry period. The survey was performed on 148 teats during the dry period, with sample collection in the period D-70 (70 days before delivery) and D14 (14 days after delivery). The milk samples were collected for the Strip Cup Test (SCT), California Mastitis Test (CMT), Microbiological Culture, Somatic Cell Count (SCC), Somatic Cell Score (SCS) and Hyperkeratosis (HK). The groups in which there were no microorganisms grow were divided into two groups, in the first group only the internal sealant in the teat was used (Group 1) and there was another group with the intramammary antibiotic use associated with the internal sealant (Group 2). Teats which were considered positive, with microbiological growth, were treated with the intramammary antibiotic associated with the internal sealant (Group 3). In the comparison of the results of the CMT test between D-70 and D14, a statistical difference was observed in Groups 2 and 3. Group 3, which comprises the positive teats in D-70 presented a reduction of 83.87% and 32.26% in the CMT test between D-70 and D14. Regarding HK, group 1 and 2 had a statistical difference in relation to group 3 in D-70 and D14. As for the numbers of bacteria isolated in D-70 and D14, there was no difference comparing Group 1 and Group 2, unlike Group 3, which had a difference. Group 1 and Group 2 were all negative teats in D-70, showing that the intramammary antibiotic did not influence the outcome of D14. In group 3 there was a reduction of isolates from 62 to 15 in D14. The most prevalent microorganism was Streptococcus agalactiae with 43.37% of the total isolates, followed by Staphylococcus aureus (16.87%) and Corynebacterium spp. (13.25%) and Coagulase negative Staphylococcus (SCN) (10.84%). The selective treatment of teats in dry dairy cows has advantages over Blanket Dry Cow Therapy by reducing the indiscriminate use of antibiotics, avoiding bacterial resistance, ensuring better milk quality and greater food safety. Antibiotics should only be used for teats with subclinical mastitis, with the microbiological culture at the end of lactation performed by fourth individual mammary.

microbiology↗

bioRxiv2019

Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in silico Peptide Mass Data

1.Over the past decade, modern methods of mass spectrometry (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. While MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem mass spectrometry (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be very time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC-MS measurements. MS1 data are then extracted and systematically tested against an in silico library of peptide mass data compiled in house. The library has been computed from the UniProt Knowledgebase Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from spectral distances between experimental and in silico peptide mass data and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient - less than two minutes per sample - and has been successfully tested by a set of 19 different microbial pathogens. The approach is rapid, accurate and automatable and holds great potential for future microbiological applications.

microbiology↗

bioRxiv2026

A low-cost rpoB-based multiplex MAMA PCR for differentiation of the Klebsiella pneumoniae species complex

The Klebsiella pneumoniae species complex (KpSC) is a clinically important group of closely related pathogens associated with invasive infections. The complex comprises seven closely related members, which are often reported as K. pneumoniae, particularly in resource-limited settings. Accurate differentiation of KpSC members remains challenging because routine laboratory methods lack sufficient resolution, and approaches like mass spectrometry and whole genome sequencing (WGS) are not widely available. Consequently, the epidemiology and clinical significance of non-K. pneumoniae members of the KpSC remain underrecognized. We developed a conventional multiplex mismatch amplification mutation assay (MAMA) PCR targeting species- and subspecies-specific single-nucleotide polymorphisms in the housekeeping gene rpoB, with six primer sets for differentiation of common KpSC members. The assay was validated against 49 genomically characterized clinical isolates, after which 179 wastewater-derived isolates provisionally identified as Klebsiella spp. by standard microbiological methods were tested. Of these, 174 were assigned to specific KpSC members by the assay, while 5 produced inconclusive amplification patterns. A subset of 16 environmental isolates was selected for WGS, including four of the five inconclusive isolates. All environmental isolates with interpretable MAMA PCR patterns were concordant with WGS. The four inconclusive environmental isolates were identified as Enterobacter spp. Overall, comparison of MAMA PCR with WGS showed 100% sensitivity and 100% specificity for all tested targets, and the total cost was approximately US$1. This rpoB-based multiplex MAMA PCR provides a simple, accurate, and low-cost approach for differentiation of KpSC members in routine laboratories and may support improved identification and surveillance in resource-limited settings. ImportanceThe Klebsiella pneumoniae species complex (KpSC) has seven members but is often reported as a single organism in routine laboratories, masking clinically and epidemiologically important diversity. As a result, the contribution of non-K. pneumoniae KpSC members to human and environmental microbiology remains poorly defined, especially in low-resource settings. We developed a conventional multiplex mismatch amplification mutation assay (MAMA) PCR based on discriminatory rpoB single nucleotide polymorphisms for differentiation of common KpSC members using standard PCR and agarose gel electrophoresis. The assay demonstrated 100% sensitivity and 100% specificity against whole-genome sequencing and excluded non-Klebsiella environmental isolates initially identified as Klebsiella pneumoniae using standard microbiological procedures. With an estimated per-test cost of about US$1, this method offers an affordable and scalable option for laboratories seeking more accurate KpSC identification and improved surveillance.

microbiology↗

bioRxiv2026

Antimicrobial Resistance Profiling and Phenotypic Characterization of Archived Clinical Bacillus paranthracis Strains

Bacillus paranthracis was formally defined as a species in 2017, after decades of carrying the name "emetic B. cereus" based on cereulide production and clustering within B. cereus sensu lato phylogenetic group III. Commonly associated with foodborne intoxication, reports rarely link B. paranthracis to non-foodborne clinical illness. As such, the new taxonomy and close resemblance of the name to the biothreat pathogen Bacillus anthracis cause confusion in diagnostic and public health settings. To address this issue, B. paranthracis clinical strains (n=20) from the CDC collection were tested with microbiological methods used for identification of B. anthracis and antimicrobial susceptibility testing. Some B. paranthracis phenotypes were similar to B. anthracis, however others were inconsistent across strains. Like B. anthracis: 3 strains tested capsule positive, 5 were non-hemolytic on blood agar, and 9 non-motile. All B. paranthracis strains were resistant to gamma phage lysis, which differentiated them from B. anthracis. Treatment regimens for B. paranthracis infections are not well established, as antimicrobial therapy is not indicated for emetic intoxication caused by B. paranthracis. Notably, six B. paranthracis strains had elevated minimal inhibitory concentrations to anthrax-recommended antibiotics: one for ciprofloxacin, three for doxycycline and tetracycline, and two for clindamycin. Rapid MinION sequencing was assessed for antimicrobial resistance detection prediction but had limited value when using PiMA v.1. These microbiological observations and susceptibility profiles of B. paranthracis expand our understanding of this pathogen, strengthening our ability to differentiate this bacterium from B. anthracis to improve diagnosis and patient outcomes. IMPORTANCEThis study describes in vitro characterization of 20 archived clinical strains of B. paranthracis, an opportunistic pathogen identified more frequently in recent reports. Our findings highlight phenotypic differences and similarities between B. paranthracis and B. anthracis using standard microbiological methods and drug susceptibility profiling. We also assess a rapid B. anthracis specific MinION long read genome sequencing workflow with B. paranthracis. This report highlights the overlapping morphological features shared by B. paranthracis and B. anthracis to improve future laboratory diagnosis and strengthen anthrax preparedness. This article will effectively reach an audience of public health professionals and microbiologists strengthening anthrax preparedness.

microbiology↗

bioRxiv2020

A CURE for physiological characterization of bacterioplankton in liquid culture

Bacterial characterization is an important aspect of microbiology that includes experimentally determining growth rates, environmental conditions conducive to growth, and the types of energy sources microorganisms can use. Researchers use this information to help understand and predict an organisms ecological distribution and environmental functions. Microbiology students generally conduct bacterial characterization experiments in their coursework; however they are frequently restricted to model organisms without ecological relevance and for which the results have been known for decades. We present a course-based undergraduate research experience (CURE) curriculum to involve students in characterization of previously untested, ecologically relevant bacterioplankton cultures to identify the carbon substrates used for growth, as well as the temperature and salinity ranges conducive to growth. Students use these results to connect their organisms physiology to the isolation environment. This curriculum also exposes students to advanced microbiology methods such as flow cytometry for measuring cell concentrations, teaches them to use the programming language R for data plotting, and emphasizes scientific communication through writing, speaking, poster creation/presentation, and social media. This CURE is an attractive introduction to scientific research and was successfully tested with 147 students during the fall semester of 2018.

scientific communication and education↗

bioRxiv2020

Reverse transcriptase enzyme and priming strategy affect quantification and diversity of environmental transcripts

RT-Q-PCR, and RT-PCR amplicon sequencing, provide a convenient, target-specific, high-sensitivity approach for gene expression studies and are widely used in environmental microbiology. Yet, the effectiveness and reproducibility of the reverse transcription step has not been evaluated. Therefore, we tested a combination of four commercial reverse transcriptases with two priming techniques to faithfully transcribe 16S rRNA and amoA transcripts from marine sediments. Both enzyme and priming strategy greatly affected quantification of the exact same target with differences of up to 600-fold. Furthermore, the choice of RT system significantly changed the communities recovered. For 16S rRNA, both enzyme and priming had a significant effect with enzyme having a stronger impact than priming. Inversely, for amoA only the change in priming strategy resulted in significant differences between the same sample. Specifically, more OTUs and better coverage of amoA transcripts diversity were obtained with GS priming indicating this approach was better at recovering the diversity of amoA transcripts. Moreover, sequencing of RNA mock communities revealed that, even though transcript diversities (i.e. OTU counts within a sample) can be biased by the RT, the comparison of {beta} diversities (i.e. differences in OTU counts between samples) is reliable as those biases are reproducible between environments. Originality-Significance StatementIs the complementary DNA (cDNA) produced after Reverse Transcription (RT) a faithful representation of the starting RNA? This is a fundamental and important question for transcriptomic-based studies in environmental microbiology that aim to quantify and/or examine the diversity of transcripts via RT approaches. Yet little is known about the reliability and reproducibility of this step. Here, we evaluated the effect of the two main components of the RT reaction - the retro transcriptase enzyme and priming strategy (gene specific vs random priming), on the quantification and diversity of cDNA. We found that both have a significant impact. We further provide evidence to enable informed choices as to the enzyme and priming combinations to improve the performance of RT-PCR approaches. Taken together, this work will improve the reliability and reproducibility of transcript-based studies in environmental microbiology.

molecular biology↗

bioRxiv2020

Stability of extemporaneously compounded amiloride nasal spray

Anxiety disorders (AD) are the most common mental illnesses affecting an estimated 40 million adults in the United States. Amiloride, a diuretic agent, has shown efficacy in treating AD in preclinical models by inhibiting the acid-sensing ion channels (ASIC). By delivering amiloride via nasal route, rapid onset of action can be achieved due to direct "nose-to-brain" access. Therefore, this study reports the formulation, physical, chemical, and microbiological stability of an extemporaneously prepared amiloride 2 mg/mL nasal spray. The amiloride nasal spray was prepared by adding 100 mg of amiloride hydrochloride to 50 mL of sterile water for injection in a sterile reagent bottle. A stability-indicating high-performance liquid chromatography (HPLC) method was developed and validated. Forced-degradation studies were performed to confirm the ability of the HPLC method to identify the degradation products from amiloride distinctively. The physical stability of the amiloride nasal spray was assessed by pH, clarity, and viscosity assessments. For chemical stability studies, samples of nasal sprays stored at room temperature were collected at time-points 0, 3 hr., 24 hr., and 7 days and were assayed in triplicate using the stability-indicating HPLC method. Microbiological stability of the nasal spray solution was evaluated for up to 7 days based on the sterility test outlined in United States Pharmacopoeia (USP) chapter 71. The stability-indicting HPLC method identified the degradation products of amiloride without interference from amiloride. All tested solutions retained over 90% of the initial amiloride concentration for the 7-day study period. There were no changes in color, pH, and viscosity in any sample. The nasal spray solutions were sterile for up to 7 days in all samples tested. An extemporaneously prepared nasal spray solution of amiloride hydrochloride (2 mg/mL) was physically, chemically, and microbiologically stable for 7 days when stored at room temperature.

pharmacology and toxicology↗

bioRxiv2020

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Scalability and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: 1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; 2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; 3) Use of high-performance and high-throughput computational platforms; 4) Generation of hierarchical population-based genotypes at different scales of resolution based on combinations of multi-locus and Bayesian statistical approaches for classification; 5) Detection of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases and association with genotypic classifications; and 6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species and the Pegasus WMS facilitates addition or removal of programs from the workflow or modification of options within them. All the dependencies of ProkEvo can be distributed via conda environment or Docker image. To demonstrate versatility of the ProkEvo platform, we performed population-based analyses from available genomes of three distinct pathogenic bacterial species as individual case studies (three serovars of Salmonella enterica, as well as Campylobacter jejuni and Staphylococcus aureus). The specific case studies used reproducible Python and R scripts documented in Jupyter Notebooks and collectively illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be used to generate novel hypotheses about the evolutionary history and ecological characteristics of specific populations of each pathogen. Collectively, our study shows that ProkEvo presents a viable option for scalable, automated analyses of bacterial populations with powerful applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

bioinformatics↗

bioRxiv2021

ORT: A workflow linking genome-scale metabolic models with reactive transport codes

MotivationNutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed. ResultsWe propose a workflow ( Omics to Reactive Transport - ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBASE and PFLOTRAN. Availability and ImplementationInteractive models available at https://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/. Microbiological data available at NCBI via BioProject ID PRJNA576070. ORT Python code available at https://github.com/subsurfaceinsights/ort-kbase-to-pflotran. KBase narrative available at https://narrative.kbase.us/narrative/71260 or static narrative (no login required) at https://kbase.us/n/71260/258 Contactrebecca.rubinstein@subsurfaceinsights.com or roelof.versteeg@subsurfaceinsights.com Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2023

Effects of isochoric freezing on quality characteristics of raw bovine milk

This study investigated the effects of isochoric freezing (IF) on the shelf-life and quality of raw bovine milk over a 5-week period. The results were compared with conventional refrigeration (RF) and refrigeration after pasteurization (HTST). The IF treatment process entailed storing liquid raw milk in isochoric chambers in thermodynamic equilibrium at -5{degrees}C /77MPa and -10{degrees}C /96MPa. Several parameters were analyzed, including microbiology count, physicochemical properties, indigenous enzyme activity, protein content, volatile organic compounds profile, and lipid degradation. Both raw and pasteurized milk experienced microbial level increases past the acceptable threshold ([≥]5.5 log CFU/mL) after 2 weeks and 5 weeks, respectively, leading to the deterioration of other parameters during storage. In comparison, microbiology count decreased significantly during storage for both IF treatment conditions but was more pronounced for the higher pressure (96MPa) treatment, leading to undetectable levels of microorganism after 5 weeks. IF treatment maintained stable pH, titratable acidity, viscosity, lipid oxidation, volatile profiles, total protein content, and lactoperoxidase activity throughout the storage period. Color was preserved during IF treatment at -5{degrees}C/77MPa; however, color was impacted during IF treatment at -10{degrees}C/96MPa. Protein structures were also modified during pressurized storage in both IF treatments. Overall, the study demonstrated that isochoric freezing could significantly increase the shelf-life of milk by reducing microbiology activity, whilst maintaining its nutritional content. These results underscore the potential role of isochoric freezing as a valuable tool in eliminating pathogens while maintaining quality characteristics similar to raw milk over long storage periods.

biochemistry↗

bioRxiv2024

Evaluation of a Real-time Plasmid Transmission Detection Pipeline

The spread of antimicrobial resistance among bacteria by horizontal plasmid transmissions poses a major challenge for clinical microbiology. Here, we evaluate a new real-time plasmid transmission detection pipeline implemented in the SeqSphere+ (Ridom GmbH, Munster, Germany) software. Within the pipeline, a local Mash plasmid database is created and Mash searches with a distance threshold of 0.001 are used to trigger plasmid transmission early warning alerts (EWA). Clonal transmissions are detected using cgMLST allelic differences. The integrated tools MOB-suite, NCBI AMRFinderPlus, CGE MobileElementFinder, pyGenomeViz, and MUMmer are used to characterize plasmids and for visual pairwise plasmid comparisons, respectively. We evaluated the pipeline using published hybrid assemblies (Oxford Nanopore Technology/Illumina) of a surveillance and outbreak dataset with plasmid transmissions. To emulate prospective usage, samples were imported in chronological order of sampling date. Different combinations of the user-adjustable parameters sketch size (1,000 vs 10,000) and plasmid size correction were tested and discrepancies between resulting clusters were analyzed with Quast. When using a sketch size of 1,000 with size correction turned on, the SeqSphere+ pipeline agreed with the published data and produced the same clonal and carbapenemase-carrying plasmid clusters. EWAs were in the correct chronological order. In summary, the developed pipeline presented here is suitable for integration into clinical microbiology settings with limited bioinformatics knowledge due to its automated analyses and alert system, which are combined with the GUI-based SeqSphere+ platform. Thus, with its integrated sample database, (near) real-time plasmid transmission detection is within reach in bacterial routine-diagnostic settings when long-read sequencing is employed. ImportancePlasmid-mediated spread of antimicrobial resistance (AMR) is a major challenge for clinical microbiology and monitoring of potential plasmid transmissions is essential to combat further dissemination. Whole-genome sequencing (WGS) is often used to surveil nosocomial transmissions but usually limited to the detection of clonal transmissions (based on chromosomal markers). Recent advances in long-read sequencing technologies enable full reconstruction of plasmids and the detection of very similar plasmids but so far easy-to-use bioinformatic tools for this purpose were missing. Here we present an evaluation of an innovative real-time plasmid transmission detection pipeline. It is integrated into the GUI-based SeqSphere+ software, which already offers cgMLST based pathogen outbreak detection. It requires very limited bioinformatics knowledge, and its database, automated analyses, and alert system make it well suited for prospective clinical application.

bioinformatics↗

bioRxiv2024

Identification and Mitigation of microbial contaminant reads from long-read metagenomic samples

Metagenomic sequencing of clinical samples has significantly enhanced our understanding of microbial communities. However, microbial contamination and host-derived DNA remain a major obstacle to accurate data interpretation. Here, we present a methodology called Stop-Check-Go for detecting and mitigating contaminants in metagenomic datasets obtained from neonatal patient samples (nasal and rectal swabs). This method incorporates laboratory and bioinformatics work combining a prevalence method, coverage estimation, and microbiological reports. We compared the Stop-Check-Go decontamination system with other published decontamination tools, and commonly found poor performance in decontaminating microbiologically negative patients (false positives). We emphasize that host DNA decreased by an average of 76% per sample using a lysis method and was further reduced during post-sequencing analysis. Microbial species were classified as putative contaminants and assigned to Stop in nearly 60% of the dataset. The Stop-Check-Go system was developed to address the specific need of decontaminating low-biomass samples, where existing tools primarily designed for short-read metagenomic data showed limited performance. Impact StatementMetagenomics has gained popularity due to its diverse applications in the multi-omics research field and the improvements in sequencing performance of technologies such as Nanopore. However, challenges in biological interpretation remain because of the complexity of the data structure and the potential of contamination occurring at multiple steps during sample processing, which can lead to incorrect conclusions. We aim to raise awareness of contamination, which can be host-associated, cross-contamination, or library-derived, any of which may be introduced at any stage from sample collection. Existing decontamination tools are largely designed for short-read sequencing and thus present limitations when applied to long-read datasets. We propose a direct comparison of species in samples with species in weekly negative controls that progressively accumulate both external and kit-reagent contaminants. Additionally, we recommend incorporating read-depth coverage and read-prevalence metrics, particularly in studies involving low-biomass or non-culturable microorganisms. Whenever possible, validation with microbiological reports is strongly advised. Our code is available on GitHub and can be executed locally in RStudio. It outputs species classifications labeled Stop, Check, or Go, as well as BIOM format files clean of identified contaminants, ready for downstream analysis with R packages such as phyloseq, vegan, or metagenomeSeq. Data summaryThe complete source code and documentation are available from GitHub (https://github.com/SAM81221/Stop-Check-Go_TAPIR). Metagenomic sequences including controls have been deposited in the ENA in project PRJEB82667; and isolate sequences of control samples in PRJEB95992. Information on samples and sequences can be found in Supplementary Table S1.

bioinformatics↗

bioRxiv2026

Stability of Oxycodone Solutions Containing S-Ketamine or Dexmedetomidine

ObjectivesTo determine whether adding S-ketamine or dexmedetomidine to oxycodone affects the microbiological, physical, or chemical stability of patient-controlled analgesia (PCA) solutions prepared in a hospital pharmacy. MethodsOxycodone solution (1 mg/mL) and three oxycodone-S-ketamine mixtures (0.25, 0.50, 0.75 mg/mL) and three oxycodone-dexmedetomidine mixtures (2.5, 5.0, 10 {micro}g/mL) were compounded under validated EU GMP Class A/B aseptic conditions and filled into PCA reservoirs. Reservoirs (n=42 for physicochemical studies; n=21 for sterility; n=4 for antimicrobial activity testing) were stored at 2-8{degrees}C for 28 days, then at 20-25{degrees}C for 2 days. Sterility was assessed by membrane filtration according to Ph. Eur. 2.6.1. Physical stability was evaluated by visual inspection, pH, weight, and osmolality. Chemical stability was assessed using a validated HPLC-UV method developed in accordance with FDA and ICH Q2(R1) guidelines. ResultsAll antimicrobial activity tests showed growth of the six reference strains, indicating no inhibition by the drug mixtures. All 21 sterility-test reservoirs remained free of turbidity throughout 30 days. No visual changes, precipitation, or discolouration were observed. Weight loss was [≤]0.3%, pH changes were between required range 4,5-7, and osmolality increased by <1.4% during the study. Measured oxycodone, S-ketamine, and dexmedetomidine concentrations remained within {+/-}5% of initial values, and no degradation products were detected. ConclusionsOxycodone PCA solutions containing S-ketamine or dexmedetomidine remained sterile, physically stable, and chemically stable for 28 days at 2-8{degrees}C followed by 2 days at room temperature at 20-25{degrees}C. These findings support extended shelf-life and centralized batch preparation of opioid-adjuvant PCA reservoirs in hospital pharmacy practice. Key MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSOpioid-adjuvant combinations such as oxycodone with S-ketamine or dexmedetomidine are increasingly used in patient-controlled analgesia, but no commercial multi-agent formulations exist. Hospital pharmacies therefore prepare these mixtures as compounded sterile preparations, despite limited data on their chemical and microbiological stability. What this study addsThis study demonstrates that oxycodone PCA solutions containing S-ketamine or dexmedetomidine remain chemically stable and microbiologically sterile for 28 days at 2-8{degrees}C plus 2 days at 20-25{degrees}C, when prepared under validated aseptic conditions. Concentrations of all analytes remained within {+/-}5% of initial values, and no degradation products were detected using a validated HPLC-UV method. How this study might affect research, practice or policyThese stability data support the assignment of extended beyond-use dates and enable centralized batch compounding of PCA reservoirs in hospital pharmacies. The findings have the potential to reduce aseptic workload, improve production efficiency and decrease medication waste while ensuring product quality.

pharmacology and toxicology↗

bioRxiv2016

An ex vivo lung model to study bronchioles infected with Pseudomonas aeruginosa biofilms

A key aim in microbiology is to determine the genetic and phenotypic bases of bacterial virulence, persistence and antimicrobial resistance in chronic biofilm infections. This requires tractable, high-throughput models that reflect the physical and chemical environment encountered in specific infection contexts. Such models will increase the predictive power of microbiological experiments and provide platforms for enhanced testing of novel antibacterial or antivirulence therapies. We present an optimised ex vivo model of cystic fibrosis lung infection: ex vivo culture of pig bronchiolar tissue in artificial cystic fibrosis mucus. We focus on the formation of biofilms by Pseudomonas aeruginosa. We show highly repeatable and specific formation of biofilms that resemble clinical biofilms by a commonly-studied lab strain and ten cystic fibrosis isolates of this key opportunistic pathogen.

Microbiology↗