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bioRxiv2025

Real-world testing of the durability claims of a commercially available spray-on surface biocide

Self-disinfecting biocidal surfaces have been proposed as a solution to prevent infections caused by the transmission of microorganisms from frequently touched surfaces in hospitals and other settings. For example, surface anchoring quaternary ammonium salt (SAQAS)-based biocides are purported to maintain their antimicrobial potency for up to 30 days and are available as spray-on formulations. We tested the 30-day potency claim of a commercially available spray-on SAQAS-based biocide ("SAQAS-A") under "real-world" conditions in a microbiology laboratory where regular cleaning is routine. To do this, we determined the background microbial burden on high-traffic floor areas, routinely used bench areas, frequently touched handles, and glass surfaces for 30 days before and after applying SAQAS-A. Experiments were repeated three times, and data was analysed using two Generalised Linear Mixed Models. We observed that for >80% of bench samples, the number of viable bacteria recovered was below the highest acceptable level of 2.5 CFU/cm2, with minimal reduction in CFU recovery observed after SAQAS-A treatment. In contrast, the number of floor and glass samples in which the microbial burden exceeded 2.5 CFU/cm2 was greater after biocide application (12.7 and 73%, respectively) than before (4.8 and 37%, respectively). Analysis of all data using two statistical models confirmed that the application of SAQAS-A had no antimicrobial effect. In conclusion, our results indicate that SAQAS-A was ineffective in preventing surface contamination over 30 days in a real-world scenario where routine cleaning occurs. ImportanceWe tested the claim that a commercially available spray-on biocide could protect surfaces from microbial contamination for 30 days. In the presence of routine disinfection, we found that spray-on applications of the surface anchoring quaternary ammonium salt-based biocide did not protect frequently touched surfaces in a working microbiology research lab for up to 30 days. Our data show that users of this type of product should be aware of the limitations of manufacturers claims of "continued protection", and manufacturers should consider formulations that more reliably attach to surfaces. Similarly, regulatory and consumer protection agencies should provide clear guidance for companies wishing to make durability and longevity claims for biocidal surface applications.

microbiology↗

bioRxiv2025

MARISMa: a routine MALDI-TOF MS database from 2018 to 2024

Clinical microbiology laboratories play a crucial role in identifying pathogens, guiding antibiotic treatment, and managing antimicrobial resistance (AMR). Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) has become essential for rapid, accurate, and cost-effective microbial identification. Recent advances in integrating MALDI-TOF MS with Artificial Intelligence (AI) show promise in improving microbial detection and prediction of AMR. However, progress is limited by the lack of comprehensive and openly accessible datasets that restrict the validation, reproducibility, and applicability of the model. To address this gap, we introduce a publicly available MALDI-TOF MS dataset comprising 202,700 unique spectra from isolates collected between 2018 and 2024 at the Hospital General Universitario Gregorio Maranon, Spain. This dataset includes 186,213 bacteria, 16,163 fungal, and 371 mycobacterial samples, of which 29,679 contain AMR annotations. This resource is openly and freely shared, rigorously curated, and designed to support a wide range of machine learning. By ensuring unrestricted access to high-quality, standardized data, this dataset aims to promote transparency, reproducibility, comparative benchmarking, and collaborative progress in AI-driven clinical microbiology.

microbiology↗

bioRxiv2025

Non-destructive label-free automated identification of bacterial colonies at the species level directly on agar media using digital holography and convolutional neural network algorithms

Objectivesthis study aimed to develop a fully automated, non-destructive and label-free identification method of bacterial colonies, directly on agar plates, using a combination of digital holography and artificial intelligence and to evaluate its performances. Methodhigh-resolution holographic images of individual colonies on translucent brain-heart agar plates were taken every 30 minutes throughout an 18-hour incubation period (530 MPx for the full plate) using a large field 1x magnification system, a partially coherent LED light source and a high-resolution CMOS sensor. A database containing 49 490 digital holograms of individual colonies from 276 clinical strains belonging to ten of the most prevalent pathogenic bacterial species was used to train the convolutional neural network (CNN). Improvement in the accuracy of the prediction from the CNN algorithms was achieved using the information at different phylogenetic levels. Resultsthe performance of the BAIO-DX solution was assessed on 232 strains belonging to the 10 species used to train the algorithms but also on 64 strains from 8 species not included in the training database. For the species included in the training dataset, this new method identified 86.6% of the strains at the species level with a positive-percent agreement of 96.5%. An additional 48% of the strains not identified at the species level could be identified at the genus level thanks to the phylogenetic interpretation of the results. Conclusionsthese first results validate this approach as a candidate to obtain a fully automated non-destructive and label-free solution for bacterial identification in clinical microbiology laboratories. IMPORTANCE STATEMENTIdentification of pathogenic bacteria by culture-based methods are typically performed using MALDI-TOF mass spectrometry or biochemical systems. While automation and interpretive algorithms based on agar plate imaging and artificial intelligence (AI) has reduced manual steps, bacterial identification is still labor-intensive. Here we developed a fully automated, non-destructive and label-free identification method of bacterial colonies at the species level, directly on agar plates, using a combination of digital holography and convolutional neural network algorithms. After training the system with 276 strains belonging to ten of the most frequent pathogenic bacterial species, the BAIO-DX solution was able to identify 86.6% of new strains from these 10 species with a positive-percent agreement of 96.5%. These thorough proof of concept shows that imaging methods coupled to AI algorithms are promising to reach a fully automated identification of a significant proportion of pathogenic bacteria and has potential to enhance diagnostic workflows in clinical microbiology.

microbiology↗

bioRxiv2025

A Multi-Tetracycline Responsive Induction System for Gene Expression in Bacillus subtilis

Well-characterized induction systems that offer tightly regulated, graded, and homogeneous control of gene expression are essential tools for basic and applied microbiology. Tetracycline- based induction systems are widely used non-toxic expression systems in bacteria, however the GRAS and industrially relevant model organism Bacillus subtilis currently lacks a tightly regulated, sensitive system that is robust to media and growth conditions. Here we adapted features of existing tetracycline induction systems to the specific requirements of B. subtilis by engineering a codon-optimized TetR repressor, enhanced promoter and operator architecture, and a modular shuttle vector enabling stable, single-copy chromosomal integration. The resulting system achieves [~]1000-fold dynamic range with minimal leakiness, using subinhibitory concentrations of anhydrotetracycline, chlortetracycline, and doxycycline as inducers in rich and minimal media as well as in colonies. We further quantify the titration parameters and non-inhibitory ranges for each inducer and growth condition, providing a well-characterized and versatile tool for inducible gene expression in B. subtilis. ImportanceBacillus subtilis is an important bacterial model organism with applications in biotechnology and industrial microbiology. However, tools for tightly controlled gene regulation that are robust to growth conditions remain limited. We developed a tetracycline-inducible system tailored to B. subtilis, providing strong, tunable expression with minimal leaky expression across diverse growth conditions. Due to its enhanced sensitivity, tight regulation, and homogeneous induction of the bacterial population, it enables precision titration of gene expression for a variety of downstream applications such as physiology studies, pathway optimization, biotechnology, and colony-based screening.

microbiology↗

bioRxiv2025

What can the current global bacterial taxonomy knowledge reveal about the actual (past and present) ecological success of each lineage?

Our up-to-date sources of the man-known microbiology are publicly available, and include, as the most complete repository, the Genome Taxonomy Database GTDB https://gtdb.ecogenomic.org/, encompassing, on one end, 196 phyla, across which, at the other end, 107,235 bacterial species have been currently defined. The intermediate ranks feature 541 classes, 1,863 orders, 4,896 families, and 23,112 genera. Such a dataset is hereby used, not as a source of DNA sequences but rather as the handiest and presently most exhaustive checklist matrix of our current taxonomical notions. In the mathematical zero assumption of an equal opportunity chance for each taxon throughout a parallel evolution, a perfectly even community featuring those values would display today, within each of the 196 phyla, the mean values that would result by dividing the actual observed ones by the number of phyla. Such a virtual assemblage would therefore have the following numbers per phylum in each of them: 2.76 classes, 9.51 orders, 24.98 families, 117.92 genera, and 547.12 species. The deltas between these set-point null hypothesis values and the truly observed and described numbers for each lineage member featured by the database (numbers of species per genus, genera per family, families per order, orders per class, and classes per phylum) can reveal how much, and in which lineages, their evolution differed from each of those mere ranks means. The comparison among the actual data also allows one to answer a series of questions: 1) What is the actually occurred uneven dynamics of evolutionary differentiation across each lineage?; 2) Which taxa are, at present, the winners of the evolutionary race?, And, have they always led the run, or when did they overtake their formerly faster competitors? 3) Are there chronological bottlenecks that violate the assumption of either a constant or of a progressive speed of evolution (i.e. is speciation to each deeper, and more modern rank, consistently faster than its former step, or is there evidence of evolutionary congestion jams?); 4) which past step turns out to have been the most determinant to shape the modern assemblages? Which ones, among the taxa dominating todays diversity, have risen up just recently (e.g. by a massive radiation from genera), and which ones had instead started or accomplished the critical expansion that still keeps them as leaders, in remote times (e.g. by class or order radiations?; 5) Which patterns characterize in this respect the lineages of the most relevant bacterial agents in food, soil, industrial, clinical and environmental microbiology? Corresponding queries are addressed for the 5,869 species of Archaea. The methods and the results of this database-mined in silico analysis are hereby presented and discussed. The dataset provided as supplementary material allows the reader to address the above aspects for any taxon of interest within the 107,235 species covered by this analysis.

microbiology↗

bioRxiv2025

IDBac: an open-access web platform and compendium for the identification of bacteria by MALDI-TOF mass spectrometry.

The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, current platforms lack meaningful ways to compare multiple properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

microbiology↗

bioRxiv2017

Real-time analysis of nanopore-based metagenomic sequencing from orthopaedic device infection

Prosthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we compare direct-from-clinical-sample metagenomic Illumina sequencing with Nanopore sequencing, and report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections.\n\nDNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination.\n\nThe majority of DNA classified (>90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing.\n\nWe demonstrate initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data. The high proportion of human DNA in extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling.

microbiology↗

bioRxiv2018

A Metagenomic Comparison of Tracheal Aspirate and Mini-Bronchial Alveolar Lavage for Assessment of Respiratory Microbiota

Lower respiratory tract infections (LRTI) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, non-infectious inflammatory syndromes resembling LRTI further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed rules-based and logistic regression models (RBM, LRM) in a derivation cohort of 20 patients with LRTI or non-infectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with non-infectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an AUC of 0.96 (95% CI = 0.86 - 1.00), the diversity metric with an AUC of 0.80 (95% CI = 0.63 - 0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI = 0.75 - 1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome and host transcriptome may hold promise as a novel tool for LRTI diagnosis.\n\nSIGNIFICANCE STATEMENTLower respiratory tract infections (LRTI) are the leading cause of infectious disease-related death worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, non-infectious respiratory syndromes that resemble LRTI further complicate diagnosis and confound targeted treatment. To address this, we developed a novel metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, airway microbiome and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.

microbiology↗

bioRxiv2019

Detection and identification of bacterial spp. from culture negative surgical site infection patients using molecular tool.

Surgical site infection (SSI) is the most common post operative infections, that sometimes cause postoperative morbidity, mortality and increase in hospital costs. Managing surgical site infections, with negative culture report in routine diagnosis is a common dilemma in microbiology. The present study was carried out to know the presence and frequencies of various bacteria in wound aspirates/ swabs of some culture negative surgical site infection patients attending a tertiary care hospital of eastern India with molecular methods. Ninety seven (97) patients with post-operative SSI whose wound swabs/ aspirate were negative in the conventional aerobic culture after 48 hrs of incubation were taken for finding the presence and identification of any bacteria in sample with 16S rRNA gene specific broad PCR and submitted to NCBI. Of the 97 patients, 16S rRNA based broad range PCR assay could able to identify the presence of bacterial pathogen in 53(54.63%) cases, out of which 29 isolates were of viable but non-culturable bacteria(VBNC), 07 were of obligatory anaerobes and 13 were of unculturable bacteria, 04 were with polybacterial infections. Some measures should be taken in the microbiology laboratory along with conventional culture, for better patient care such as, culture plates should be allowed to incubate for an additional 3 - 4 days that will allow the growth any fastidious bacteria, anaerobic culture system should be developed along with aerobic system, and molecular diagnosis by 16S broad range PCR should be performed routinely.

microbiology↗

bioRxiv2019

Approaches by Rhodotorula mucilaginosa from a chronic kidney disease patient for elucidating the pathogenicity profile by this emergent species

BackgroundTraditionally known as a common contaminant, Rhodotorula mucilaginosa is among the leading causes of invasive fungal infections by non-candida yeasts. They affect mainly immunocompromised individuals, often mimicking the cryptococcosis infection, despite invasive infections by Rhodotorula are still not well explained. Thus, here we aimed to characterize microbiologically clinical isolates of R. mucilaginosa isolated from colonization of a patient with chronic renal disease (CKD), as well as to evaluate their phylogeny, antifungal susceptibility, virulence, and pathogenicity in order to infer the potential to become a possible infection.\n\nMethodology/Principal FindingsFor this study, two isolates of R. mucilaginosa from oral colonization of a CKD patient were isolated, identified and characterized by classical (genotypic and phenotypic) methods. Susceptibility to conventional antifungals was evaluated, followed by biofilm production, measured by different techniques (total biomass, metabolic activity, colony forming units and extracellular matrix quantification). Finally, the pathogenicity of yeast was evaluated by infection of Tenebrio molitor larvae.\n\nAll isolates were resistant to azole and sensitive to polyenes and they were able to adhere and form biofilm on the abiotic surface of polystyrene. In general, similar profiles among isolates were observed over the observed periods (2, 24, 48 and 72 hours). Regarding extracellular matrix components of biofilms at different maturation ages, R. mucilaginosa was able to produce eDNA, eRNA, proteins, and polysaccharides that varied according to time and the strain. The death curve in vivo model showed a large reduction in the survival percentage of the larvae was observed in the first 24 hours, with only 40% survival at the end of the evaluation.\n\nConclusions/SignificanceWe infer that colonization of chronic renal patients by R. mucilaginosa offers a high risk of serious infection. And also emphasize that the correct identification of yeast is the main means for an efficient treatment.\n\nAuthor SummaryThe genus Rhodotorula is known to be a common contaminant, however, it has been increasing in the last years, reports of different forms infections by this yeast, reaching mainly individuals with secondary diseases or with low immunity. However, very little is known about the mechanism that triggers the disease. Thus, this study aims to characterize microbiologically clinical isolates of R. mucilaginosa isolated from a patient with chronic renal disease, as well as to evaluate their phylogeny, antifungal susceptibility, virulence, and pathogenicity in order to infer the potential to become a possible infection. It was possible to characterize in general the clinical isolates, to determine that they are resistant to an important class of the antifungal agents which are the azoles. In addition, they are able to adhere and to form biofilm on abiotic surfaces, this skill represents an important factor of virulence, which would guarantee their presence in medical devices, such as catheters, surfaces. These biofilm works as true reservoirs of these fungi disseminate and cause serious infections. This pathogenic potential was reinforced by a great reduction of survival in the larvae infected with this yeast. Therefore our results infer a high risk of infection to patients who are colonized by R. mucilaginosa.

microbiology↗

bioRxiv2019

Fungal seed pathogens of wild chili peppers possess multiple mechanisms to tolerate capsaicinoids

The wild chili pepper Capsicum chacoense produces the spicy defense compounds known as capsaicinoids, including capsaicin and dihydrocapsaicin, antagonistic to the growth of fungal pathogens. Compared to other microbes, fungi isolated from infected seeds of C. chacoense possess much higher tolerance to these spicy compounds, having their growth slowed, but not entirely inhibited. Previous research has shown capsaicinoids inhibit microbes by disrupting ATP production via the binding of NADH dehydrogenase in the Electron Transport Chain (ETC), throttling Oxidative Phosphorylation (OXPHOS). Capsaicinoids may also disrupt cell membranes. Here, we investigated capsaicinoid tolerance in fungal seed pathogens isolated from C. chacoense. We selected 16 fungal isolates from four Ascomycete genera (Alternaria, Colletotrichum, Fusarium and Phomopsis). Using relative growth rate as a readout for tolerance, fungi were challenged with ETC inhibitors to infer if fungi possess alternative respiratory enzymes, and if effects on the ETC fully explained inhibition by capsaicinoids. In all isolates, we found evidence for at least one alternative NADH dehydrogenase. In many isolates we also found evidence for an alternative oxidase. These data suggest wild plant pathogens may be a rich source of alternative respiratory enzymes. We further demonstrate these fungal isolates are capable of the breakdown of capsaicinoids. Lastly, we determine the OXPHOS theory weakly explains the primary mechanism by which dihydrocapsaicin slows fungal growth, but not capsaicin. Our findings suggest capsaicinoids likely disrupt membranes in addition to energy poisoning, with implications for microbiology and human health.\n\nImportancePlants make chemical compounds to protect themselves. For example, chili peppers produce the spicy compound capsaicin to inhibit animal feeding and pathogen damage. In humans, capsaicin binds to a membrane channel protein, creating the sensation of heat, while in microbes, capsaicin limits energy production by binding respiratory enzymes. However, some data suggest capsaicin also disrupts membranes. Here we studied fungal pathogens (Alternaria, Colletotrichum, Fusarium, and Phomopsis) isolated from a wild chili pepper, Capsicum chacoense. By measuring growth rate in the presence of antibiotics with known respiratory targets, we infer wild plant pathogens may be rich with alternative respiratory enzymes. A zone of clearance around the colonies, as well as LCMS data, further indicate these fungi can break down capsaicin. Lastly, the total inhibitory effect of capsaicin was not fully explained by its effect on respiratory enzymes. Our findings lend credence to studies proposing capsaicin may disrupt cell membranes, with implications for microbiology as well as human health.

microbiology↗

bioRxiv2019

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

BackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a one-stop test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.\n\nMethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ( participants) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.\n\nResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.\n\nConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

microbiology↗

bioRxiv2019

Integration of absolute multi-omics reveals translational and metabolic interplay in mixed-kingdom microbiomes.

Microbiology is founded on well-known model organisms. For example, the majority of our fundamental knowledge regarding the quantitative levels of DNA, RNA, and protein backdates to keystone pure culture-based studies. Nowadays, meta-omic approaches allow us to directly access the molecules that constitute microbes and microbial communities, however due to a lack of absolute measurements, many original culture-derived "microbiology statutes" have not been updated or adapted to more complex microbiome settings. Within a cellulose-degrading and methanogenic consortium, we temporally measured genome-centric absolute RNA and protein levels per gene, and obtained a protein-to-RNA ratio of 102-104 for bacterial populations, whereas Archaeal RNA/protein dynamics (103-105: Methanothermobacter thermoautotrophicus) were more comparable to Eukaryotic representatives humans and yeast. The linearity between transcriptome and proteome had a population-specific change over time, highlighting a minimal subset of four functional carriers (cellulose degrader, fermenter, syntrophic acetate-oxidizer and methanogen) that coordinated their respective metabolisms, cumulating in the overarching community phenotype of converting polysaccharides to methane. Our findings show that upgrading multi-omic toolkits with traditional absolute measurements unlocks the scaling of core biological questions to dynamic and complex microbiomes, creating a deeper insight into inter-organismal relationships that drive the greater community function.

microbiology↗

bioRxiv2019

Evaluation of MALDI-ToF Mass Spectrometry for Rapid Detection of Cereulide from Bacillus cereus Cultures

1.Bacillus cereus plays an often unrecognized role in food borne diseases. Food poisoning caused by this pathogen is manifested by either diarrhea or emesis. While different enterotoxins have been linked to the diarrheal type of B. cereus infections, the emetic toxin cereulide is responsible for the second type. Due to the relatively high prevalence of cereulide associated food poisoning, methods for simple and reliable detection of cereulide producing strains are of utmost importance. Currently, liquid-chromatography coupled to mass spectrometry (LC-MS) is used for sensitive, specific and quantitative cereulide detection, but this technique requires specialized LC-MS equipment, which is often not available in microbiology routine diagnostic laboratories. The last decade has witnessed the advent of matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-ToF MS) as a simple, rapid and cost-efficient technique for identification of microbial pathogens in routine diagnostics. Just recently, two different studies reported on the application of MALDI-ToF MS for either the differentiation of emetic and non-emetic strains of B. cereus or for direct detection of cereulide from bacterial colony smears. However, no method evaluation and optimization was performed in frame of these studies. Thus, additional investigations on the selectivity and sensitivity of MALDI-TOF MS for cereulide detection are needed before implementation of this method in routine diagnostics can be considered. These aspects prompted us to investigate open or controversial issues and to systematically test sample preparation methods, commonly used for microbial identification for their suitability to detect the emetic toxin directly from bacteria. Based on our experimental findings we propose a MALDI-ToF MS workflow that allows identification of B. cereus and sensitive detection of cereulide in parallel, using standard, linear-mode MALDI-ToF MS equipment. The experimental protocol is based on the well-established ethanol/formic acid extraction method and offers, if required, possibilities for further characterization by more sophisticated LC-MS-based methods. In summary, the ease of use and the achieved level of analytical sensitivity as well as the wide-spread availability of standard MALDI-ToF MS equipment in clinical microbiological laboratories provides a promising tool to improve and to facilitate routine diagnostics of B. cereus associated food intoxications.

microbiology↗

bioRxiv2025

Isolation of Crenothrix bacteria reveals the distinct ecophysiologies of filamentous methanotrophs and adaptations to redox stress

At the dawn of modern microbiology, Cohn observed abundant filamentous bacteria in drinking water wells that he named Crenothrix polyspora. Subsequent research has revealed the methanotrophic metabolism of Crenothrix bacteria and their disproportionately high activity in stratified lakes compared to unicellular strains, yet laboratory cultivation has proven elusive, leaving the ecophysiology of Crenothrix bacteria largely unknown. Here we report the isolation of two methanotroph strains of the "lacustrine Crenothrix" clade from an iron-rich wetland and reveal their highly unique cell biologies and potential ecological roles. Using physiological approaches, we demonstrate that the strains perform a microaerobic methane metabolism while growing distinct filaments having wide and directionally oriented connective structures. The strains further have broad genomic repertoires for addressing redox stress that we show are uniquely associated with lacustrine Crenothrix compared to related methanotrophs based on genome data. Aligning with laboratory observations, we identify lacustrine Crenothrix bacteria along potential redox gradients in the wetland at iron-rich snow sites, and we further detect such bacteria in diverse global ecosystems based on public metagenome searches. Together, our data strongly point to an ecophysiology of lacustrine Crenothrix bacteria that is tightly linked to redox stress, and we propose these bacteria may uniquely store or share metabolic intermediates via their filamentous lifestyle to thrive under such conditions. Our results provide a fresh view of the diversity, evolution, and ecology of aerobic methanotrophs, connecting over 150 years of microbiology research opening vast new opportunities to probe bacterial adaptations that drive global methane cycling under redox stress.

microbiology↗

bioRxiv2026

Isolation and Characterization of a Novel Calcium-Precipitating Alkali-Tolerant Lysinibacillus sphaericus in Local Urban Environment

Concrete is an extensively used construction material in infrastructures due to cost-effectiveness and durability. However, its low tensile strength makes it prone to cracking, posing persistent maintenance challenges. Traditional repair methods are often expensive and difficult to implement, especially for critical structures. Recent studies propose a potential solution involving alkaliphilic or alkali-tolerant calcium-carbonate producing bacteria in aiding concrete crack repair through microbial-induced calcium carbonate precipitation (MICP) via urea hydrolysis. Considering the adaptive nature of bacteria, we hypothesize that naturally occurring concrete-inhabiting microbes possess properties crucial for mending cracks. Therefore, this study aims to isolate and evaluate these inherent microbes and their MICP ability. Six concrete samples were collected and cultured on Alkaline Nutrient Agar for microbial isolation. Urease activity was assessed phenotypically and genotypically. MICP activity was observed and validated under Scanning Electron Microscope/Energy Dispersive Spectroscopy (SEM/EDS). Out of the 49 isolates cultured, Lysinibacillus sphaericus PUMA0250 emerges as the most promising isolate for practical implementation, showing high pH survivability in an in-house formulated concrete agar medium (pH 12.6). L. sphaericus PUMA0250 exhibited MICP activity via urea hydrolysis and harbored all crucial genes involved in urease-mediated MICP. SEM/EDS analysis confirmed the structure and composition of the produced calcium carbonate precipitate. This study demonstrates the potential of L. sphaericus PUMA0250 to be incorporated into concrete to assess its healing efficiency. Its ability to thrive in the alkaline concrete environment and produce calcium by-products may aid concrete crack repair, opening microbiological avenues for sustainable and efficient concrete repair methodologies. IMPORTANCEAlthough concrete is widely used in construction, the construction material is prone to cracking, leading to costly repairs and structural degradation. This study isolated Lysinibacillus sphaericus PUMA0250 from tropical urban concrete, that can survive the highly alkaline environment typical of concrete structures in equatorial climate. Importantly, it produces calcium carbonate, a mineral that can help in concrete repair. These findings contribute to our understanding of how microbes that naturally produce calcium carbonate by-products can be used to repair concrete. For such applications, microbes must be able to withstand extreme conditions, including high pH and low nutrient availability. Our discovery of a resilient, native isolate highlights the potential of tropical concrete microbiomes as sources for self-healing construction technologies. This work lays the foundation for more sustainable, low-maintenance building materials and opens new possibilities in microbiology-driven solutions for urban infrastructure challenges.

microbiology↗

bioRxiv2026

Automated Optimization of Bacterial Tracking Pipelines with TrackMate 8

Quantitative analysis of bacterial dynamics in time-lapse microscopy requires robust tracking pipelines, yet selecting and optimizing algorithms for specific experiments remains challenging. Indeed, Microbiologists are confronted with numerous algorithms that must be carefully chosen and parameterized to achieve optimal tracking for their experiments. We present an automated methodology to determine optimal tracking configurations for microbiological applications. It is based on TrackMate 8, a novel version of the TrackMate Fiji plugin extended with microbiology-specific tools. Our approach systematically evaluates algorithm-parameter combinations optimizing biologically relevant metrics (e.g., cell-cycle accuracy, bacteria morphology) and includes: (1) integration of deep-learning algorithms (Omnipose, YOLO, Trackastra) adequate for bacteria images in TrackMate, (2) a TrackMate-Helper extension for parameter optimization, and (3) a tracking and segmentation editor for tracking ground-truth generation. We demonstrate the effectiveness of the methodology on two use cases showing its adaptability to diverse experimental conditions. This methodology enables microbiologists with a widely applicable, automated framework to optimize tracking pipelines, facilitating quantitative analysis in bacterial imaging.

microbiology↗

bioRxiv2026

The historical domestication of a Clostridium botulinum strain used for the industrial production of botulinum neurotoxin

Laboratory production of botulinum neurotoxin (BoNT) began more than 90 years ago for medical, military, and later pharmaceutical applications, creating one of the longest-running examples of microbial cultivation under sustained human control. A single Clostridium botulinum Group I lineage, Army Hall A (AHA), was established by the U.S. military in 1942 and later gave rise to Hall A-hyper (HAH), the strain widely used for pharmaceutical BoNT production. We analyzed more than 1,000 C. botulinum genomes to identify AHAs closest relatives and to infer the most recent common ancestor (MRCA) shared with its nearest wild lineage. Relative to this MRCA, AHA accumulated nearly 100 genetic changes, including 46 single-nucleotide substitutions, 44 small insertions or deletions, and several large deletions and structural variants that led to the loss of more than 80 genes. A nonsense mutation in mutS generated a hypermutator phenotype that accelerated mutation rates and increased genetic diversity. This event occurred early in the lineages domestication and appears to have facilitated laboratory-adaptive traits, including the lack of sporulation and increased BoNT yield. Competition experiments under standard growth conditions confirmed substantial laboratory adaptation, with AHA exhibiting a strong fitness advantage over a close wild relative. Together, these results reconstruct the genomic trajectory of a bacterium evolving under prolonged human-mediated selection and provide a genome-resolved example of microbial domestication. The findings show how laboratory conditions, industrial selection, and changing mutation rates can jointly shape bacterial evolution, and they offer a general framework for understanding domestication and laboratory adaptation across microbial systems. SignificanceHuman-mediated species domestication has been central to the development of civilization, with well-known examples in plants and animals. Microbes have also been domesticated, often unintentionally and before the advent of modern microbiology. The military and pharmaceutical applications of botulinum neurotoxin led to the sustained cultivation and eventual domestication of a high toxin-producing Clostridium botulinum strain that remains widely used today. We reconstruct the genomic changes along this trajectory and identify a key early mutation that generated a hypermutator phenotype, increasing genetic variation available for human-directed selection. These findings reveal fundamental evolutionary processes shaping bacterial genomes under long-term human control. This genome-resolved example of microbial domestication offers a general framework for understanding laboratory adaptation in both evolutionary and applied microbiology.

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