Daan Korporaal, Patrick de Kruijf, Ralph H. G. M. Litjens
et al.
The detection and classification of bacterial colonies in images of agar-plates is important in microbiology, but is hindered by the lack of labeled datasets. Therefore, we propose Colony Grounded SAM2, a zero-shot inference pipeline to detect and segment bacterial colonies in multiple settings without any further training. By utilizing the pre-trained foundation models Grounding DINO and Segment Anything Model 2, fine-tuned to the microbiological domain, we developed a model that is robust to data changes. Results showed a mean Average Precision of 93.1\% and a $Dice@detection$ score of 0.85, showing excellent detection and segmentation capabilities on out-of-distribution datasets. The entire pipeline with model weights are shared open access to aid with annotation- and classification purposes in microbiology.
Microorganisms are ubiquitous in nature, and microbial activities are closely intertwined with the entire life cycle system and human life. Developing novel technologies for the detection, characterization and manipulation of microorganisms promotes their applications in clinical, environmental and industrial areas. Over the last two decades, terahertz (THz) technology has emerged as a new optical tool for microbiology. The great potential originates from the unique advantages of THz waves including the high sensitivity to water and inter-/intra-molecular motions, the non-invasive and label-free detecting scheme, and their low photon energy. THz waves have been utilized as a stimulus to alter microbial functions, or as a sensing approach for quantitative measurement and qualitative differentiation. This review specifically focuses on recent research progress of THz technology applied in the field of microbiology, including two major parts of THz biological effects and the microbial detection applications. In the end of this paper, we summarize the research progress and discuss the challenges currently faced by THz technology in microbiology, along with potential solutions. We also provide a perspective on future development directions. This review aims to build a bridge between THz photonics and microbiology, promoting both fundamental research and application development in this interdisciplinary field.
The study of microorganisms, or microbiology, has demonstrated significant development since its inception and is currently a key field of biological sciences that has a huge impact on modern society and scientific research. Over the centuries, this discipline has undergone significant changes, shaping our understanding of infectious diseases and food safety. Starting from the simplest observations of microscopic organisms such as bacteria, viruses, fungi and protozoa, and ending with modern molecular and genomic research methods. This article describes a brief historical path of microbiology development. The heuristic, morphological, physiological, immunological, and molecular genetic stages are the main periods into which the development of this science is traditionally divided, despite the lack of full-fledged and precise boundaries between them.
Fateme Nateghi Haredasht, Fatemeh Amrollahi, Manoj Maddali
et al.
The Antibiotic Resistance Microbiology Dataset (ARMD) is a de-identified resource derived from electronic health records (EHR) that facilitates research in antimicrobial resistance (AMR). ARMD encompasses big data from adult patients collected from over 15 years at two academic-affiliated hospitals, focusing on microbiological cultures, antibiotic susceptibilities, and associated clinical and demographic features. Key attributes include organism identification, susceptibility patterns for 55 antibiotics, implied susceptibility rules, and de-identified patient information. This dataset supports studies on antimicrobial stewardship, causal inference, and clinical decision-making. ARMD is designed to be reusable and interoperable, promoting collaboration and innovation in combating AMR. This paper describes the dataset's acquisition, structure, and utility while detailing its de-identification process.
Alba Muñoz del Río, Víctor Casero-Alonso, Mariano Amo-Salas
This study addresses from the Optimal Experimental Design perspective the use of the isothermal experimentation procedure to precisely estimate the parameters defining models used in predictive microbiology. Starting from a case study set out in the literature, and taking the Baranyi model as the primary model, and the Ratkowsky square-root model as the secondary, D- and c-optimal designs are provided for isothermal experiments, taking the temperature both as a value fixed by the experimenter and as a variable to be designed. The designs calculated show that those commonly used in practice are not efficient enough to estimate the parameters of the secondary model, leading to greater uncertainty in the predictions made via these models. Finally, an analysis is carried out to determine the effect on the efficiency of the possible reduction in the final experimental time.
Margarita Safonova, Bharat Chandra P, Binukumar G. Nair
et al.
The Earth possesses many environmental extremes that mimic conditions on extraterrestrial worlds. The stratosphere at 30-40 km altitude closely resembles the surface of Mars in terms of pressure, temperature, and radiation levels (UV, proton, and Galactic cosmic rays). While microbial life in the troposphere is well documented, the true upper limit of Earth's biosphere remains unclear. The stratosphere offers a promising environment to explore microbial survival in such extreme conditions. Despite its significance to astrobiology, this region remains largely unexplored due to difficulties in access and avoiding contamination. To address this, we have developed SAMPLE (Stratospheric Altitude Microbiology Probe for Life Existence), a balloon-borne payload designed to collect dust samples from the stratosphere and return them in conditions suitable for lab analysis. The entire system is novel and designed in-house, with weight- and stress-optimized components. The main payload includes three pre-sterilized sampling trays and a controller that determines altitude and governs tray operation. One tray will remain closed during flight (airborne control) and another on the ground (cleanroom control) to monitor contamination. Additional systems include environmental sensors, GPS trackers, cameras, and a Flight Termination Unit (FTU) to end the mission once sampling is complete. A parachute ensures the safe recovery of the payload. Upon retrieving the payload, the sampling trays (including controls) will be sent to a suitable laboratory where the samples will be examined for the presence and nature of collected material.
Advancements in artificial intelligence (AI) have transformed many scientific fields, with microbiology and microbiome research now experiencing significant breakthroughs through machine learning applications. This review provides a comprehensive overview of AI-driven approaches tailored for microbiology and microbiome studies, emphasizing both technical advancements and biological insights. We begin with an introduction to foundational AI techniques, including primary machine learning paradigms and various deep learning architectures, and offer guidance on choosing between traditional machine learning and sophisticated deep learning methods based on specific research goals. The primary section on application scenarios spans diverse research areas, from taxonomic profiling, functional annotation \& prediction, microbe-X interactions, microbial ecology, metabolic modeling, precision nutrition, clinical microbiology, to prevention \& therapeutics. Finally, we discuss challenges in this field and highlight some recent breakthroughs. Together, this review underscores AI's transformative role in microbiology and microbiome research, paving the way for innovative methodologies and applications that enhance our understanding of microbial life and its impact on our planet and our health.
The SSPACE Astrobiology Payload (SAP) series, starting with the SAP-1 project is designed to conduct in-situ microbiology experiments in low earth orbit. This payload series aims to understand the behaviour of microbial organisms in space, particularly those critical for human health, and the corresponding effects due to microgravity and solar/galactic radiation. SAP-1 focuses on studying Bacillus clausii and Bacillus coagulans, bacteria beneficial to humans. It aims to provide a space laboratory for astrobiology experiments under microgravity conditions. The hardware developed for these experiments is indigenous and tailored to meet the unique requirements of autonomous microbiology experiments by controlling pressure, temperature, and nutrition flow to bacteria. A rotating platform, which forms the core design, is innovatively utilised to regulate the flow and mixing of nutrients with dormant bacteria. The technology demonstration models developed at SSPACE have yielded promising results, with ongoing efforts to refine, adapt for space conditions, and prepare for integration with nanosatellites or space modules. The anticipated payload will be compact, approximately 1U in size (10cm x 10cm x 10cm), consume less than 5W power, and offer flexibility for various microbiological studies.
For more than 3.5 billion years, life experienced dramatic environmental extremes on Earth. These include shifts from oxygen-less to over-oxygenated atmospheres and cycling between hothouse conditions and global glaciations. Meanwhile, an ecological revolution took place. The planet evolved from one dominated by microbial life to one containing the plants and animals that are most familiar today. The activities of many key cellular inventions evolved early in the history of life, collectively defining the nature of our biosphere and underpinning human survival. There is a critical need for a new disciplinary synthesis to reveal how microbes and their molecular systems survived ever changing global conditions over deep time. This review critically examines our current understanding of early microbial life and describes the foundations of an emerging area in microbiology and evolutionary synthetic biology to reconstruct the earliest microbial innovations.
Nicolas Fares, Maxime Lavaud, Zaicheng Zhang
et al.
Confined motions in complex environments are ubiquitous in microbiology. These situations invariably involve the intricate coupling between fluid flow, soft boundaries, surface forces and fluctuations. In the present study, such a coupling is investigated using a novel method combining holographic microscopy and advanced statistical inference. Specifically, the Brownian motion of softmicrometric oil droplets near rigid walls is quantitatively analyzed. All the key statistical observables are reconstructed with high precision, allowing for nanoscale resolution of local mobilities and femtonewton inference of conservative or non-conservative forces. Strikingly, the analysis reveals the existence of a novel, transient, but large, soft Brownian force. The latter might be of crucial importance for microbiological and nanophysical transport, target finding or chemical reactions in crowded environments, and hence the whole life machinery.
Catarina Leal, Ales Eichmeier, Kateřina Štůsková
et al.
With a reduction in available chemical treatments, there is an increased interest in biological control of grapevine trunk diseases. Few studies have investigated the impact of introducing beneficial microorganisms in the rhizosphere on the existing indigenous soil microbiome. In this study, we explored the effect of two biocontrol agents (BCAs), Trichoderma atroviride SC1 (Ta SC1) (Vintec; Certis Belchim) and Bacillus subtilis PTA-271 (Bs PTA-271), on the grapevine rhizosphere bacterial and fungal microbiome as well as plant defense expression using high-throughput amplicon sequencing and quantitative real-time polymerase chain reaction (PCR), respectively. Additionally, we quantified both Ta SC1 and Bs PTA-271 in the rhizosphere over time using droplet digital PCR. The fungal microbiome was more affected by factors such as soil type, BCA treatment, and sampling time compared with the bacterial microbiome. Specifically, Ta SC1 application produced negative impacts on fungal diversity, whereas application of BCAs did not affect bacterial diversity. Interestingly, the survival and establishment of both BCAs showed opposite trends depending on the soil type, indicating that the physicochemical properties of soils have a role in BCA establishment. Fungal co-occurrence networks were less complex than bacterial networks but highly impacted by Ta SC1 application. Soils treated with Ta SC1 presented more complex and stable co-occurrence networks, with a higher number of positive correlations. Induced grapevine defenses also differed according to the soil, being more affected by BCA inoculation on sandy soil. The findings of this research emphasize the complex relationships among microorganisms in the rhizosphere and highlight the significance of taking into account various factors, such as soil type, sampling time, and BCA treatment, and their influence on the structure and dynamics of microbial communities.
Mercy Hokah Kibathi, Mercy Hokah Kibathi, Edith Chepkorir
et al.
BackgroundYellow fever virus (YFV) and dengue virus (DENV) are among the major re-emerging arboviruses that pose a significant threat to public health. Their associated burden and prevalence can be substantially underestimated due to insufficient surveillance and inadequate diagnosis. This study aimed to determine evidence of dengue, yellow and related flaviviruses circulation among the rural human populations residing in Nguruman (Kajiado County) and Kerio Valley (Baringo County), two dryland ecosystems in the Kenyan Rift Valley.MethodsSerum samples obtained from febrile patients between 5 and 85 years through a hospital-based cross-sectional survey from July 2020 – May 2023, were screened for neutralizing antibodies to YFV, DENV-2 and related flaviviruses, West Nile virus (WNV) and Zika virus (ZIKV) via Plaque reduction neutralization test (PRNT). The study sites and important demographic characteristics were obtained using a structural questionnaire and the data analyzed and seroprevalence compared. A multinomial logistic regression model was done to predict risk for each of the most prevalent viruses with covariates; age, gender, and occupation.ResultsOverall, 54.5% (50.1–59.0% 95% confidence interval (CI) of the samples tested positive for at least one of the four Flaviviruses. The percentage was significantly higher in Kerio Valley (64.34%, 184/286) than in Nguruman (40.2%, 78/194) (P<0.0001). YFV had the highest prevalence, followed by WNV (16.25%), ZIKV (5.2%), and DENV-2 (1%). Kerio Valley had a significantly higher YFV seroprevalence (51%) than Nguruman (6%) (P<0.0001), while DENV-2 was observed only in Nguruman with a low seropositivity of 2%. In contrast to Nguruman, where seropositivity rates were higher in males at 47.47% (P=0.049), in Kerio Valley, females showed considerably higher viral seropositivity at 60.82% than males (P<0001).ConclusionThe study suggests that there is significant circulation of Flaviviruses in both regions, posing a public health risk, that could potentially contribute to clinical disease. However, seropositivity rates vary for each specific site. Furthermore, there could be a risk of YFV, WNV, and ZIKV transmission in both sites with DENV transmission specifically noted in Nguruman. The study findings inform direct cost-effective actions (such as YF vaccines) and precise surveillance data of vector populations for improved disease risk prediction.
Armin D. Tavakkoli, BA, Megan A. Clark, BE, Alireza Kheirollah, PhD
et al.
Purpose: Ultra High Dose-Rate (UHDR) radiation has been reported to spare normal tissue, compared with Conventional Dose-Rate (CDR) radiation. However, important work remains to be done to improve the reproducibility of the FLASH effect. A better understanding of the biologic factors that modulate the FLASH effect may shed light on the mechanism of FLASH sparing. Here, we evaluated whether sex and/or the use of 100% oxygen as a carrier gas during irradiation contribute to the variability of the FLASH effect. Methods and Materials: C57BL/6 mice (24 male, 24 female) were anesthetized using isoflurane mixed with either room air or 100% oxygen. Subsequently, the mice received 27 Gy of either 9 MeV electron UHDR or CDR to a 1.6 cm2 diameter area of the right leg skin using the Mobetron linear accelerator. The primary postradiation endpoint was time to full thickness skin ulceration. In a separate cohort of mice (4 male, 4 female), skin oxygenation was measured using PdG4 Oxyphor under identical anesthesia conditions. Results: Neither supplemental oxygen nor sex affected time to ulceration in CDR irradiated mice. In the UHDR group, skin damage occured earlier in male and female mice that received 100% oxygen compared room air and female mice ulcerated sooner than male mice. However, there was no significant difference in time to ulceration between male and female UHDR mice that received room air. Oxygen measurements showed that tissue oxygenation was significantly higher when using 100% oxygen as the anesthesia carrier gas than when using room air, and female mice showed higher levels of tissue oxygenation than male mice under 100% oxygen. Conclusions: The skin FLASH sparing effect is significantly reduced when using oxygen during anesthesia rather than room air. FLASH sparing was also reduced in female mice compared to male mice. Both tissue oxygenation and sex are likely sources of variability in UHDR studies. These results suggest an oxygen-based mechanism for FLASH, as well as a key role for sex in the FLASH skin sparing effect.
Medical physics. Medical radiology. Nuclear medicine, Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Saber Mirzaee Bafti, Chee Siang Ang, Gianluca Marcelli
et al.
A diversified dataset is crucial for training a well-generalized supervised computer vision algorithm. However, in the field of microbiology, generation and annotation of a diverse dataset including field-taken images are time consuming, costly, and in some cases impossible. Image to image translation frameworks allow us to diversify the dataset by transferring images from one domain to another. However, most existing image translation techniques require a paired dataset (original image and its corresponding image in the target domain), which poses a significant challenge in collecting such datasets. In addition, the application of these image translation frameworks in microbiology is rarely discussed. In this study, we aim to develop an unpaired GAN-based (Generative Adversarial Network) image to image translation model for microbiological images, and study how it can improve generalization ability of object detection models. In this paper, we present an unpaired and unsupervised image translation model to translate laboratory-taken microbiological images to field images, building upon the recent advances in GAN networks and Perceptual loss function. We propose a novel design for a GAN model, BioGAN, by utilizing Adversarial and Perceptual loss in order to transform high level features of laboratory-taken images into field images, while keeping their spatial features. The contribution of Adversarial and Perceptual loss in the generation of realistic field images were studied. We used the synthetic field images, generated by BioGAN, to train an object-detection framework, and compared the results with those of an object-detection framework trained with laboratory images; this resulted in up to 68.1% and 75.3% improvement on F1-score and mAP, respectively. Codes is publicly available at https://github.com/Kahroba2000/BioGAN.
Healthcare-Associated Infections present a major threat to patient safety globally. According to studies, more than 50% of HAI could be prevented by proper hand hygiene. Effectiveness of hand hygiene is regularly evaluated with the fluorescent method: performing hand hygiene with a handrub containing an ultra violet (UV) fluorescent marker. Typically, human experts evaluate the hands under UV-A light, and decide whether the applied handrub covered the whole hand surface. The aim of this study was to investigate how different experts judge the same UV-pattern, and compare that to microbiology for objective validation. Hands of volunteer participants were contaminated with high concentration of a Staphylococcus epidermidis suspension. Hands were incompletely disinfected with UV-labeled handrub. Four different UV-box type devices were used to take CCD pictures of the hands under UV light. Size of inadequately disinfected areas on the hands were determined in two different ways. First, based on microbiology; the areas where colonies were grown were measured. Second, four independent senior infection control specialists were asked to mark the missed areas on printed image, captured under UV light. 8 hands of healthy volunteers were examined. Expert evaluations were highly uncorrelated (regarding interrater reliability) and inconsistent. Microbiology results weakly correlated with the expert evaluations. In half of the cases, there were more than 10% difference in the size of properly disinfected area, as measured by microbiology versus human experts. Considering the result of the expert evaluations, variability was disconcertingly high. Evaluating the fluorescent method is challenging, even for highly experienced professionals. A patient safety quality assurance system cannot be built on these data quality.
Soil drench treatment using <i>Paenibacillus polymyxa</i> strain KN-03 was applied to citrus plants infected with <i>Candidatus</i> Liberibacter asiaticus (<i>C</i>Las). The infection status was assessed using PCR and a real-time quantitative PCR detection system (qPCR). The application of KN-03 resulted in a notable reduction in <i>C</i>Las levels in citrus plants. Specifically, by the 257th day post treatment commencement, following 24 KN-03 applications, the negative rates of <i>C</i>Las in the vein, root tip, and shoot tip were 50%, 0%, and 50%, respectively. After 24 cycles, KN-03 application significantly enhanced plant growth and stimulated reactive oxygen production in citrus leaves compared to control plants. Transcriptome analysis identified specific upregulated pathways. Furthermore, flora analysis revealed an increased abundance of microorganisms possessing potential utilization value, including <i>Burkholderia-Caballeronia-Paraburkholderia</i>, <i>uncultured_bacterium_o_Acidobacteriales</i>, <i>uncultured_bacterium_f_Gemmatimonadaceae</i>, and <i>Rhodanobacter</i>, in the root zone. Moreover, the BugBase analysis indicated that KN-03 treatment increased the abundance of beneficial rhizosphere bacteria associated with biofilm formation, element mobilization, and stress tolerance. These findings support the utility of <i>Paenibacillus polymyxa</i> KN-03 as an effective plant-growth-promoting bacterium for <i>C</i>Las management, with additional benefits for plant growth and soil health, specifically offering detoxification resources for shoot tip grafting.