Environmental Samples Research Articles

Comparison of Different Vibrational Spectroscopic Probes (ATR-FTIR, O-PTIR, Micro-Raman, and AFM-IR) of Lipids and Other Compounds Found in Environmental Samples: Case Study of Substrate-Deposited Sea Spray Aerosols

Comparison of Different Vibrational Spectroscopic Probes (ATR-FTIR, O-PTIR, Micro-Raman, and AFM-IR) of Lipids and Other Compounds Found in Environmental Samples: Case Study of Substrate-Deposited Sea Spray Aerosols

Isoliquiritigenin induced hepatotoxicity and endoplasmic reticulum stress in zebrafish embryos.

Isoliquiritigenin (ISL), a naturally occurring flavonoid derived from licorice root, exhibits antioxidant, anticancer, anti-inflammatory, and anti-allergic properties, and is frequently detected in both environmental and human samples. Previous studies from our lab have demonstrated that ISL exposure can lead to developmental deformities and aberrant immune responses. However, the molecular mechanisms underlying ISL toxicity in zebrafish embryos remain incompletely elucidated. Therefore, this study aimed to elucidate the effects of ISL exposure on endoplasmic reticulum (ER) stress in zebrafish embryos by assessing the expression levels of ER stress markers HSPA5 and CHOP, along with associated apoptosis factors, under various ISL concentrations, with tunicamycin (TM) serving as a positive control. Furthermore, targeted analyses of ER stress-related pathways were conducted using RNA transcriptome sequencing, and the up-regulated gene was verified by western blot. The results revealed that ISL exposure significantly elevated the expression levels of HSPA5 and CHOP, concomitantly activating ER stress pathways, including pPERK-eIF2α-ATF4 and ATF6 pathways in zebrafish embryos. These findings suggest that the activation of endoplasmic reticulum stress signaling pathways may contribute to the developmental deformities observed in zebrafish embryos following ISL exposure, thereby highlighting the potential ecological risks associated with ISL usage.

The transmission routes of African swine fever during an outbreak in Serbia July–August 2023: African swine fever virus detections in environmental samples and insects

African swine fever (ASF) is a highly contagious viral disease of domestic pigs and wild boar (Sus scrofa) caused by an arbovirus- African swine fever virus (ASFV), which is classified into the family Asfarviridae. Even though the main transmission route of ASFV is direct contact between animals and carcasses releasing ASFV into the environment, the role of other transmission routes such as via environmental contamination or insects remains in great part unclear. During an epidemic f ASF in Serbia in 2023, environmental samples (soil, feed, water and swabs from the pig barns), and insects [resulting in collection of adult and/or larval stages of non-biting flies (Diptera: Calliphoridae and Muscidae)] were collected in four locations in South Banat district of Serbia. To assess the possibility that insects carry the ASFV in infected courtyards, sticky fly traps and open Petri dishes containing meat mixed with humid cotton wads were offered in three locations during the five days of the experiment in the Belgrade area. Furthermore, to confirm the role of flies in ASF in mechanical transmission pathway in Serbia, L2 and L3 larvae of flies (Lucilia sericata Meigan, 1826; Stomoxys calcitrans Linnaeus, 1758) were collected from the pig carcasses from infected farms, bred to adults in the Laboratory and an ASFV spiked meat meal was placed into cages with three-day-old flies (n = 52) to estimate positivity of flies and duration of mechanical transmission of ASFV. The results from the environmental samples showed no positive ASFV DNA detection, the same was true for the samples from meat-based traps and sticky fly traps, while ASFV DNA was detected in three samples containing eggs, L1 and L3 fly larvae collected from carcasses and adult flies (L. sericata). In experimental conditions, only one S. calcitrans fly tested positive on day 1 post-infection. The results implicate the possible role of Lucilia sp. flies in the mechanical transmission of ASFV as well as S. calcitrans in Serbia during an outbreak, while ASFV DNA was not detected in environmental samples in this study.

Building an eDNA surveillance toolkit for invasive rodents on islands: can we detect wild-type and gene drive Mus musculus?

Invasive management strategies range from preventing new invasive species incursions to eliminating established populations, with all requiring effective monitoring to guide action. The use of DNA sampled from the environment (eDNA) is one such tool that provides the ability to surveille and monitor target invasive species through passive sampling. Technology being developed to eliminate invasive species includes genetic biocontrol in the form of gene drive. This approach would drive a trait through a population and could be used to eliminate or modify a target population. Once a gene drive organism is released into a population then monitoring changes in density of the target species and the spread of the drive in the population would be critical. In this paper, we use invasive Mus musculus as a model for development of an eDNA assay that detects wild-type M. musculus and gene drive M. musculus. We demonstrate successful development of an assay where environmental samples could be used to detect wild-type invasive M. musculus and the relative density of wild-type to gene drive M. musculus. The development of a method that detects both wild-type M. musculus and a gene drive M. musculus (tCRISPR) from environmental samples expands the utility of environmental DNA. This method provides a tool that can immediately be deployed for invasive wild M. musculus management across the world. This is a proof-of-concept that a genetic biocontrol construct could be monitored using environmental samples.

An Overview of Microfluidic‐assisted Strategies for Synthesis and Applications of Molecularly Imprinted Polymers

This review gives an overview of using microfluidics in conjunction with molecularly imprinted polymers (MIP), which covers two aspects: on the one hand, on‐chip synthesis of polymer and MIP particles on the nano and the micro scale. This comprises both approaches using two different immiscible solvents and homogeneous matrices to obtain the desired particle morphologies. On the other hand, especially paper‐based microfluidic systems have attracted increasing interest as low‐cost analytical tools that are inherently useful for applying at the point of care. By now, there have been several successful attempts to combine them with MIP (instead of biological recognition systems) and to successfully apply them in environmental samples, food matrices, and for diagnostic applications.

Occurrence and assemblage distribution of Giardia Duodenalis in symptomatic and asymptomatic patients in southeastern Iran (2019-2022).

The ubiquitous protozoan parasite Giardia duodenalis is a major contributor to the global burden of diarrhoea, particularly in young children living in poor-resource regions. Although rarely mortal, giardiasis is associated with growth retardation and cognitive impairment in early childhood. Here we investigate the epidemiology of human giardiasis in Iranshahr (south-eastern Iran), a region where this information was previously lacking. Stool samples were collected from 17,455 outpatients and inpatients attended at three major hospital settings during April 2020 and March 2022. Microscopy was used as a screening method for the presence of Giardia cysts, and the identification of G. duodenalis assemblages was carried out using PCR and Sanger sequencing. The overall prevalence of giardiasis was 1.87 (326/17,455; 95% CI: 1.7-2.1). Being female was positively associated with higher odds of giardiasis (p = 0.014). Individuals without diarrhoea were less likely to have giardiasis (p = 0.022). Individuals attending the Iran Hospital were more likely to harbour G. duodenalis infections compared to those attending at the Khatam Hospital and the Clinical Reference Laboratory (p = 0.001). Our sequence analyses revealed the presence of assemblages A (56.5%, 13/23), B (39.1%, 9/23), and A + B (4.4%, 1/23). No association was observed between the occurrence of a given assemblage and the occurrence of diarhroea. Giardia infections were found at relatively low prevalence rates in both symptomatic and asymptomatic individuals seeking medical attention. Being female, having diarrhoea, and being sampled during 2020-21 were predictors of giardiasis. Although limited, our molecular data indicate that some Giardia infections may be zoonotic in nature. These data should be corroborated and expanded in future epidemiological studies targeting simultaneously human, animal, and environmental (water) samples to improve our understanding of the epidemiology of giardiasis in Iran.

Comparison of commonly used software pipelines for analyzing fungal metabarcoding data.

Metabarcoding targeting the internal transcribed spacer (ITS) region is commonly used to characterize fungal communities of various environments. Given their size and complexity, raw ITS sequences are necessarily processed and quality-filtered with bioinformatic pipelines. However, such pipelines are not yet standardized, especially for fungal communities, and those available may produce contrasting results. While some pipelines cluster sequences based on a specified percentage of base pair similarity into operational taxonomic units (OTUs), others utilize denoising techniques to infer amplicon sequencing variants (ASVs). While ASVs are now considered a more accurate representation of taxonomic diversity for prokaryote communities based on 16S rRNA amplicon sequencing, the applicability of this method for fungal ITS sequences is still debated. Here we compared the performance of two commonly used pipelines DADA2 (inferring ASVs) and mothur (clustering OTUs) on fungal metabarcoding sequences originating from two different environmental sample types (fresh bovine feces and pasture soil). At a 99% OTU similarity threshold, mothur consistently identified a higher fungal richness compared to DADA2. In addition, mothur generated homogenous relative abundances across multiple technical replicates (n = 18), while DADA2 results for the same replicates were highly heterogeneous. Our study highlights a potential pipeline-associated bias in fungal metabarcoding data analysis of environmental samples. Based on the homogeneity of relative abundances across replicates and the capacity to detect OTUs/ASVs, we suggest using OTU clustering with a similarity of 97% as the most appropriate option for processing fungal metabarcoding data.

VeTAPRH: A Taxonomic Assignment Protocol for Vertebrates Applied to eDNA Metabarcoding Data, Including Molecular, Taxonomic and Ecological Criteria

Exploring biodiversity requires meticulous species identification within specific environments. Environmental DNA (eDNA) refers to DNA extracted from environmental samples (Taberlet et al. 2018). Using metabarcoding with eDNA enables detailed taxonomic inventories (Valentini et al. 2009, Haderlé et al. 2024). After sample collection, DNA is extracted, the targeted barcode is amplified, and obtained amplicons are sequenced, producing millions of sequences. Bioinformatics processing is then a particularly important step in the analysis used to clean, structure sequences and complete taxonomic assignments. However, computerized protocols face limitations, including taxonomic misidentifications due to intraspecific variation, such as in the Delphininae (Alfonsi et al. 2013), or incomplete reference databases (e.g. Hleap et al. 2021, Meglécz 2023). Relying on custom databases may help but can miss unexpected taxa range shifts (Gold et al. 2021, Jung et al. 2016). Including ecological data (Coissac et al. 2012, Deiner et al. 2017, Blackman et al. 2023) or integrating multiple databases (Bourret et al. 2023) enhances accuracy, and expert validation remains essential (Clarke et al. 2017, Porter and Hajibabaei 2018). Our study aims to develop a taxonomic assignment protocol for vertebrate Molecular Operational Taxonomic Units (MOTUs)/Amplicon Sequence Variants (ASVs), called VeTAPRH (Vertebrates Taxonomic Assignment Protocol), to verify automated assignments from metabarcoding pipelines. This protocol generates successive species lists, first built on the basis of molecularly similar taxa, then successively refined on the basis of taxonomic data and plausibility of local distribution, compiled from specialized databases. By cross-referencing these criteria, we establish a list of hypothetical taxa for each MOTU, including those absent from reference databases. Initially presented as a flowchart, this protocol will lay the groundwork for a digital tool to support taxonomists.

Multi-class cyanobacterial toxin analysis using hydrophilic interaction liquid chromatography-mass spectrometry.

Cyanobacteria produce diverse classes of toxins including microcystins, nodularins, anatoxins, cylindrospermopsins and saxitoxins, encompassing a range of chemical properties and mechanisms of toxicity. Comprehensive analysis of these toxins in cyanobacterial, environmental and biological samples generally requires multiple methods of extraction and analysis. In this work, a method was developed for the major classes of cyanotoxins, which comprised of a three-step liquid-solid extraction method using 75 % CH3CN with 0.1 % HCOOH and a hydrophilic interaction liquid chromatography (HILIC) elution gradient that provided retention of the less polar microcystins through to the highly polar saxitoxins. Detection was performed by tandem mass spectrometry in selected reaction monitoring mode with positive and negative polarity switching. Identification criteria included matching retention times and product ion ratios with available standards. In-house validation demonstrated good performance of the method including precision ranging from 1.5 (microcystin-LA) to 5.8 (gonyautoxin-2) % RSDs, and detection limits ranging from 0.01 (cylindrospermopsin) to 0.99 (gonyautoxin-3) µg/g in freeze dried material cyanobacteria. Recovery was assessed using spiked non-toxic cyanobacterial samples (Aphanizomenon sp.) and ranged from 83 (neosaxitoxin) to 107 % ([Dha7]microcystin-LR). As a demonstration of application, toxin profiles in cyanobacterial cultures, benthic and planktonic cyanobacteria field samples, and shellfish reference materials were successfully evaluated. The procedure is also amenable for extension to other polar toxin classes including domoic acid and guanitoxin. With increasing reports of cyanobacterial blooms globally, the method represents a powerful quantitative screening tool for measuring cyanotoxins across a broad range of samples.

Comparison of reference libraries for the detection of tire-derived microplastics (TMPs)

ABSTRACT Introducing microplastics (MPs) into the marine environment is a global problem. Tire-derived microplastics (TMPs) are estimated to account for 60% of all secondary MPs dispersed in aquatic environments. To effectively detect TMPs in environmental samples using micro-Fourier transform infrared (μFTIR) spectroscopy, a high-quality reference library is essential. However, the use of conventional diamond crystals in FTIR presents challenges for the detection of materials containing carbon black, such as rubber and tires. In addition, there is a discrepancy between spectra from standard libraries and spectra from environmental samples, which makes detection difficult. In order to overcome these problems in the detection of TMPs by μFTIR, we developed four reference libraries to improve the detection, and ‘The 26 tire wear library’ was found to be the best among these four. Furthermore, a comparison of these new libraries revealed the following requirements to improve TMP detection: (i) the reference spectra must be acquired under the same setup used for material observation including prism material, (ii) tires, not rubber, must be used as reference materials, and (iii) tire wear samples must be prepared to replicate the actual generation conditions on roads.

Construction of Mo-Doped CuO Incorporated on Carbon Black Modified Disposable Sensor for the Voltammetric Detection of Metol in Environmental Samples

Abstract In this study, a molybdenum-doped copper oxide (Mo–CuO) composite was synthesized via a hydrothermal method and combined with carbon black (CB) to form Mo–CuO@CB. This composite was used to modify a screen-printed carbon electrode (SPCE) for the detection of Metol (MT), an industrial pollutant harmful to both human health and the environment. Structural and surface characterization was performed using high-resolution transmission electron microscopy, field-effect scanning electron microscopy, energy-dispersive spectroscopy, Raman spectroscopy, X-rssy photoelectron spectroscopy, and X-ray diffraction. Electrochemical techniques, including differential pulse voltammetry and cyclic voltammetry, were used to assess the sensor's performance. The Mo–CuO@CB@SPCE sensor exhibited a low detection limit of 2.7 nM, and limit of quantification is 82 nM, a broad linear range (5.0 × 10−9 – 170 mol L-1), and high sensitivity (4.148 μA μM⁻¹ cm⁻²), benefiting from the catalytic activity of Mo–CuO and the large surface area of CB. With recovery rates ranging from 96 % to 100.6% in pond, river, and tap water, the sensor effectively detects MT in environmental samples, ensuring reliable monitoring of this persistent pollutant.

Deep-Eutectic-Solvent-Decorated Metal–Organic Framework for Food and Environmental Sample Preparation

Deep eutectic solvent (DES) is distinguished by its unique solvent properties, chemical stability, and eco-friendly nature, which are pivotal in a spectrum of chemical processes. It enhances the sample preparation process by increasing efficiency and minimizing the environmental impact. Metal–organic frameworks (MOFs), which are porous structures formed through coordination bonds between metal ions and organic ligands, are defined by their adjustable pore dimensions, extensive surface areas, and customizable architectures. The integration of DES within MOF to create DES@MOF capitalizes on the beneficial attributes of both materials, augmenting MOFs’ stability and versatility while providing a multifunctional carrier for DES. This composite material is both highly stable and readily tunable, establishing it as a leading contender for applications in sample preparation for food and environmental samples. This comprehensive review explores the application of DES-decorated MOF in food and environmental sample preparation and highlights the expansive potential of DES@MOF in diverse fields. We provide a detailed analysis of the characteristics of DES@MOF and its individual components, methods for decorating MOFs with DES, the advantages of these composite materials in sample pretreatment, and their specific applications in food safety and environmental monitoring. DESs are employed to modify MOFs, offering a multitude of benefits that can substantially improve the overall performance and applicability of MOFs. The review also discusses current challenges and future directions in this field, offering valuable insights for further research and development. The synergistic effects of DES and MOFs offer new opportunities for applications in food safety and other areas, leading to the development of more efficient, sensitive, and environmentally friendly analytical methods. This collaboration paves the way for sustainable technologies and innovative solutions to complex challenges.

Machine Learning-Assisted Surface-Enhanced Raman Spectroscopy Detection for Environmental Applications: A Review.

Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance its appeal for widespread application. However, challenges such as the management of voluminous quantities of high-dimensional data, its capacity to detect low-concentration targets in the presence of environmental interferents, and the navigation of the complex relationships arising from overlapping spectral peaks have emerged. In response, there is a growing trend toward the use of machine learning (ML) approaches that encompass multivariate tools for effective SERS data analysis. This comprehensive review delves into the detailed steps needed to be considered when applying ML techniques for SERS analysis. Additionally, we explored a range of environmental applications where different ML tools were integrated with SERS for the detection of pathogens and (in)organic pollutants in environmental samples. We sought to comprehend the intricate considerations and benefits associated with ML in these contexts. Additionally, the review explores the future potential of synergizing SERS with ML for real-world applications.

An intelligent spectral identification approach for the simultaneous detection of endocrine-disrupting chemicals in aquatic environments.

With the rapid progression of industrialization, the application and release of endocrine disruptors (EDCs), including bisphenol A (BPA), octylphenol and nonylphenol have significantly increased, presenting substantial health hazards. Conventional analytical techniques, such as high-performance liquid chromatography and gas chromatography-mass spectrometry, are highly sophisticated but suffer from complex procedures and high costs. To overcome these limitations, this study introduces an innovative spectral methodology for the simultaneous detection of multiple aquatic multicomponent EDCs. By leveraging chemical machine vision, specifically with convolutional neural network (CNN) models, we employed a long-path holographic spectrometer for rapid, cost-effective identification of BPA, 4-tert-octylphenol, and 4-nonylphenol in aqueous samples. The CNN, refined with the ResNet-50 architecture, demonstrated superior predictive performance, achieving detection limits as low as 3.34, 3.71 and 4.36 μg/L, respectively. The sensitivity and quantification capability of our approach were confirmed through the analysis of spectral image Euclidean distances, while its universality and resistance properties were validated by assessments of environmental samples. This technology offers significantly advantages over conventional techniques in terms of efficiency and cost, offering a novel solution for EDC monitoring in aquatic environments. The implications of this research extend beyond improved detection speed and cost reduction, presenting new methodologies for analyzing complex chemical systems and contributing to environmental protection and public health.

Using polymerase chain reaction cycle threshold (PCR Ct) values for predicting and managing cholera outbreaks: potential, challenges, and future directions

Abstract Background Cholera continues to be a major public health threat, especially in regions with poor sanitation and limited access to clean water. Accurate prediction and management of cholera outbreaks are essential to reduce mortality and morbidity. This review focuses on the potential of polymerase chain reaction (PCR) cycle threshold (Ct) values as an innovative tool for early detection and control of cholera outbreaks, specifically highlighting its utility in predicting outbreaks and guiding public health responses. Main body of abstract PCR Ct values offer a significant advantage in the early detection of Vibrio cholerae, the pathogen responsible for cholera, in both clinical and environmental samples. By providing quantitative data on bacterial load, lower Ct values indicate a higher concentration of the pathogen, signaling the potential for increased disease transmission. These values allow for more precise, real-time monitoring of cholera outbreaks and aid in targeting intervention strategies such as water sanitation improvements, vaccination campaigns, and antibiotic treatments. Moreover, the application of Ct values in environmental surveillance, particularly in monitoring water sources, offers a proactive approach to prevent the spread of cholera by identifying contamination risks before human cases arise. However, the implementation of PCR in low-resource settings faces significant challenges, including high costs, the need for advanced laboratory infrastructure, and a lack of technical expertise. Addressing these barriers through cost-effective innovations and capacity building initiatives is crucial for optimizing the use of PCR Ct values in cholera management. Conclusion PCR Ct values hold great promise for improving cholera outbreak prediction and control. Despite challenges in adopting this technology in resource-limited settings, the integration of Ct value monitoring into public health frameworks can enhance early detection efforts and contribute to more effective cholera management strategies.

Antimicrobial resistance, virulence factors and phylogenetic profiles of Vibrio parahaemolyticus in the eastern coast of Shenzhen

Vibrio parahaemolyticus (V. parahaemolyticus) is a major food-borne pathogen which causes human gastroenteritis. Since the characteristics of V. parahaemolyticus remain unknown, 220 isolates selected from clinical and environmental samples in Dapeng of Shenzhen were tested for the presence of two hemolysin-expressing genes tdh and trh. Among 27 clinical isolates, 26 carrired the tdh gene, and the other one carried both tdh and trh genes, however neither genes were detected in environmental isolates. Meanwhile, antimicrobial susceptibility profiles revealed the isolates with high frequency of resistance to ampicillin (77.73%) and colistin (71.82%) and medium to streptomycin (57.27%). Genetically, by whole genome sequencing (WGS), comparative genomics studies was performed on isolates from various districts and GenBank. Data analysis showed that antimicrobial resistance genes (ARGs) blaCARB, tet(34) and tet(35) were harbored in all genomes and other ARGs was absent in the genomes of 27 clinical isolates. Besides, little regional difference was observed. As for virulence factors, MAM7, T3SS1, T3SS1 secret effector, T3SS2, T3SS2 secret effector, and VpadF were carried by most isolates. Two isolates from other districts were tdh gene positive which clustered with clinical isolates from Dapeng in the same clade, indicating close genetic distance. This study revealed the widely distribution of V. parahaemolyticus in Shenzhen and the diverse ARGs and virulence genes it carried. Furthermore, pathways that pathogen disseminated through were discussed.

Nursery origin and propagation stage influence the endophytic fungal communities inhabiting grapevine planting stocks

Infection of grapevine trunk disease (GTD) pathogens can occur in nursery and may result in young vine decline in newly established vineyards. We aimed at profiling the causal agents of GTD in California nurseries and explore how the vine propagation processes affect pathogens spread and fungal community dynamics. Plant and environmental samples were collected throughout the plant propagation. For grafted vines, wood tissue samples were collected above the graft union (scion), below the graft union (rootstock) and at the crown (rootstock) and wood necrosis was scored using a 0-3 rating system. We used both a metabarcoding approach using PCR primers custom-designed for GTDs and culturing technique coupled with Sanger sequencing for sample diagnosis. Results showed that mycobiome diversity and composition in vines was significantly influenced by the nursery of origin and the propagation stage. We identified 21 GTD-taxa across all plant samples associated with Petri disease, black foot, Botryosphaeria dieback, Phomopsis dieback and Eutypa dieback. Only 10% of the mother vines cuttings were GTD-pathogens free but co-infection with multiple pathogens became more frequent as the vines progressed through the propagation pipeline. Especially, the incidence of pathogens associated with Petri disease (Phaeoacremonium, Cadophora, Pleurostoma) and Fusarium increased during that time span likely because of high contamination levels in soil and water environments. Wood necrosis at the graft union and crown also increased post grafting and Phaeoacremonium and Fusarium correlated with more necrosis whereas Trichoderma with healthier wood ratings. Our study suggests that nursery practices strongly influence GTD pathogen profile.

Bacterial diversity in rice field soil and sludge soil samples: A comparative metagenomics-based study

Abstract Soil contains several organic and inorganic substances. It also has a large number of microbial diversity including bacteria. This microbial community affects the physicochemical properties of soil. This bacterial bacteria diversity is also involved in biomass degradation and plant growth promotion. Metagenomic sequencing is used to analyze microbial diversity in environmental samples. The metagenomic profiling of bacterial populations in the sludge and rice field soil was done at phylum, class, order, family, genus, and species levels. The metagenomic study revealed that Proteobacteria, Bacteroidetes, Chloroflexi, Acidobacteria and other unknown bacteria were reported in 16S rRNA Illumina MiSeq in the sludge and rice soil samples. We compared the taxonomic classification of bacterial diversity found in sewage soils with that of rice field soils using metagenomic sequencing analysis of the V3-V4 region of the 16S rRNA. In rice soil, the most abundant group was Proteobacteria followed by Chloroflexi, Acidobacteria, Actinobacteria, and Bacteroidetes which increase the soil nutrient and influence the production of the plant. Bacteroidetes are the most dominant group in sludge soil than rice soil. Consequently, the core microbiome analysis indicated that Sorangium, Geobacter, Azoarcus, and Anaeromyxobacter bacterial genera were more abundant in both soil samples.

Artificial Intelligence-Assisted Automatic Raman-Activated Cell Sorting (AI-RACS) System for Mining Specific Functional Microorganisms in the Microbiome.

The microbiome represents the natural presence of microorganisms, and exploring, understanding, and leveraging its functions will bring about significant breakthroughs in life sciences and applications. Raman-activated cell sorting (RACS) enables the correlation of phenotype and genotype at the single-cell level, offering a solution to the bottleneck in microbial community functional analysis caused by challenges in cultivating diverse microorganisms. However, current labor-intensive manual procedures fall short in catering to the demands of single-cell functional analysis in microbial communities. To address this issue, we developed an artificial intelligence-assisted Raman-activated cell sorting system (AI-RACS) that integrates precise single-cell positioning, automated data collection, optical tweezers capture, and single-cell printing to elevate microbial single-cell RACS from manual to automated, validating the efficacy of the system by isolating aluminum-tolerant microbes from acidic soil microbiota. Leveraging the AI-RACS framework, we sorted 13 strains from red soil samples under near-in situ conditions, with all demonstrating strong aluminum tolerance. AI-RACS efficiently segregates microbial cells from intricate environmental samples, investigating their functional attributes and presenting a novel tool for microbial research and applications.

Investigating surface area and recovery efficiency of healthcare-associated pathogens to optimize composite environmental sampling.

Hospital surfaces are known to contribute to the spread of healthcare-associated antimicrobial pathogens. Environmental sampling can help locate reservoirs and determine intervention strategies, although sampling and detection can be labor intensive. Composite approaches may help reduce time and costs associated with sampling and detection. We investigated optimum surface areas for sampling antimicrobial-resistant organisms (AROs) with a single side of cellulose sponge, created theoretical composites (TC) by adding recovery results from multiple optimum areas, then compared the TC to the standard Centers for Disease Control and Prevention sampling method (one sponge using all sides, whole tool; (WT)). Five AROs were evaluated: carbapenemase-producing KPC+ Klebsiella pneumoniae (KPC), Acinetobacter baumannii (AB), methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus faecalis (VRE) and Clostridioides difficile spores (CD). Steel coupons comprising four surface areas (323; 645; 1,290 and 2,258 cm2) were inoculated, dried, and sampled with one sampling pass using the larger side (face) or the smaller side (edge) of a pre-moistened cellulose sponge tool. Based on the optimum areas determined for each organism, composite areas were 1,290 cm2 for MRSA and VRE, 1,936 cm2 for AB, 2,580 cm2 for CD spores and 3,870 cm2 for KPC. Total colony forming units (CFU) recovered using a composite approach was greater or comparable than using multiple WT samplings (over the same area as the composite) for MRSA, VRE and AB (130%; 144% and 95%) yet less than if using multiple WT samplings for KP and CD (47% and 66%). We propose a conservative composite sampling strategy if the target organism is unknown; 323 cm2 sampling area for each of the four sides of the sponge, (1290 cm2 total). The conservative composite sampling strategy improved the recovery of KP (from 47% to 85% of multiple WT samplings), while MRSA, VRE, AB and CD (131%; 144%; 97% and 66%) remained within 5% to that of the optimum area TC.