Beta-Hemolytic Bacteria Selectively Trigger Liposome Lysis, Enabling Rapid and Accurate Pathogen Detection

Elucidating Bacterial Spore Dynamics through Lanthanide-Enhanced Live Imaging

Identifying and distinguishing dormant and active bacterial spores are vital for biosecurity, food safety, and space exploration. Yet, there is a lack of simple, quick, and nondestructive methods to achieve this. The common Schaeffer-Fulton method is both sample-destructive and requires significant operator involvement. In this study, we employed lanthanide-beta-diketonate complexes to directly observe both dormant and germinated single spores. Staining is instantaneous and requires minimal sample processing. The complex stains areas outside the core of dormant spores, leaving the core hollow and nonfluorescent. However, upon germination, the complex enters the core, making it brightly fluorescent. This difference was noted in five bacterial species including Bacillus, Clostridium, and Clostridioides. Various lanthanides and beta-diketonates can be mixed to form a range of spore-visualizing complexes. Due to their low toxicity, these complexes allow for live imaging of single germinating spores. We demonstrate low-cost imaging using a USB microscope as well as imaging of spores in milk matrices. This method provides a valuable tool for studying bacterial spores.

Biological effect abundance analysis of hemolytic pathogens based on engineered biomimetic sensor

Conventional pathogen detection strategies based on the molecular structure or chemical characteristics of biomarkers can only provide the "physical abundance" of microorganisms, but cannot reflect the "biological effect abundance" in the true sense. To address this issue, we report an erythrocyte membrane-encapsulated biomimetic sensor cascaded with CRISPR-Cas12a (EMSCC). Taking hemolytic pathogens as the target model, we first constructed an erythrocyte membrane-encapsulated biomimetic sensor (EMS). Only hemolytic pathogens with biological effects can disrupt the erythrocyte membrane (EM), resulting in signal generation. Then the signal was amplified by cascading CRISPR-Cas12a, and more than 6.67 × 104-fold improvement in detection sensitivity compared to traditional erythrocyte hemolysis assay was achieved. Notably, compared with polymerase chain reaction (PCR) or enzyme linked immunosorbent assay (ELISA)-based quantification methods, EMSCC can sensitively respond to the pathogenicity change of pathogens. For the detection of simulated clinical samples based on EMSCC, we obtained an accuracy of 95% in 40 samples, demonstrating its potential clinical value.

Genomic Landscape Highlights Molecular Mechanisms Involved in Silicate Solubilization, Stress Tolerance, and Potential Growth-Promoting Activity of Bacterium Enterobacter sp. LR6

Silicon (Si) is gaining widespread attention due to its prophylactic activity to protect plants under stress conditions. Despite Si's abundance in the earth's crust, most soils do not have enough soluble Si for plants to absorb. In the present study, a silicate-solubilizing bacterium, Enterobacter sp. LR6, was isolated from the rhizospheric soil of rice and subsequently characterized through whole-genome sequencing. The size of the LR6 genome is 5.2 Mb with a GC content of 54.9% and 5182 protein-coding genes. In taxogenomic terms, it is similar to E. hormaechei subsp. xiangfangensis based on average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH). LR6 genomic data provided insight into potential genes involved in stress response, secondary metabolite production, and growth promotion. The LR6 genome contains two aquaporins, of which the aquaglyceroporin (GlpF) is responsible for the uptake of metalloids including arsenic (As) and antimony (Sb). The yeast survivability assay confirmed the metalloid transport activity of GlpF. As a biofertilizer, LR6 isolate has a great deal of tolerance to high temperatures (45 °C), salinity (7%), and acidic environments (pH 9). Most importantly, the present study provides an understanding of plant-growth-promoting activity of the silicate-solubilizing bacterium, its adaptation to various stresses, and its uptake of different metalloids including As, Ge, and Si.

Label-free visible colorimetric biosensor for detection of multiple pathogenic bacteria based on engineered polydiacetylene liposomes

Bacterial infections are considered as a critical healthcare concern worldwide. Timely infection detection is crucial to effective antibiotic administration which can reduce the severity of infection and the occurrence of antibiotic resistance. We have developed label-free polydiacetylene (PDA) liposome-based colorimetric biosensor to detect and identify bacterial cultures at the genus and species level with naked eyes by simple color change. We found that among the various liposomal systems, moderate concentration of PDA, phospholipids and cholesterol in liposome assemblies can greatly influence the sensitivity to different bacteria, exhibiting unique chromatic properties of each bacterial strain. The strikingly different chromatic color change was due to the various mechanisms of interactions between bacterial toxins and biomimetic lipid bilayers. Furthermore, increase of cholesterol in liposome assemblies greatly enhanced the sensitivity of bacterial strains related to membrane destruction mediated by pore-formation mechanism such as S. aureus and E.coli, whereas the detection of the two bacterial strains was believed to rely on the specific recognition elements coupled with PDA moiety. As a proof of concept, a colorimetric finger-print array for distinguishing 6 bacterial species was studied. Particularly, the proposed bacterial detection platform is achieved through the interaction between bacterially secreted toxins and liposome bilayers instead of specific recognition of receptors-ligands. The results of both response time and sensitivity of label-free-liposome-based system show superior to previous reports on chromatic bacterial detection assays. By combing these results, the label-free-liposome-based colorimetric sensing platform shows great importance as a bacterial-sensing and discrimination platform.

Multiplexed detection and differentiation of bacterial enzymes and bacteria by color-encoded sensor hydrogels

We report on the fabrication and characterization of color-encoded chitosan hydrogels for the rapid, sensitive and specific detection of bacterial enzymes as well as the selective detection of a set of tested bacteria through characteristic enzyme reactions. These patterned sensor hydrogels are functionalized with three different colorimetric enzyme substrates affording the multiplexed detection and differentiation of α-glucosidase, β-galactosidase and β-glucuronidase. The limits of detection of the hydrogels for an observation time of 60 min using a conventional microplate reader correspond to concentrations of 0.2, 3.4 and 4.5 nM of these enzymes, respectively. Based on their different enzyme expression patterns, Staphylococcus aureus strain RN4220, methicillin-resistant S. aureus (MRSA) strain N315, both producing α-glucosidase, but not β-glucuronidase and β-galactosidase, Escherichia coli strain DH5α, producing β-glucuronidase and α-glucosidase, but not β-galactosidase, and the enterohemorrhagic E. coli (EHEC) strain E32511, producing β-galactosidase, but none of the other two enzymes, can be reliably and rapidly distinguished from each other. These results confirm the applicability of enzyme sensing hydrogels for the detection and discrimination of specific enzymes to facilitate differentiation of bacterial strains. Patterned hydrogels thus possess the potential to be further refined as detection units of a multiplexed format to identify certain bacteria for future application in point-of-care microbiological diagnostics in food safety and medical settings.

Phylogenetic analyses of Norwegian Tenacibaculum strains confirm high bacterial diversity and suggest circulation of ubiquitous virulent strains

Tenacibaculosis is a bacterial ulcerative disease affecting marine fish and represents a major threat to aquaculture worldwide. Its aetiological agents, bacteria belonging to the genus Tenacibaculum, have been present in Norway since at least the late 1980’s and lead to regular ulcerative outbreaks and high mortalities in production of farmed salmonids. Studies have shown the presence of several Tenacibaculum species in Norway and a lack of clonality in outbreak-related strains, thus preventing the development of an effective vaccine. Hence, a thorough examination of the bacterial diversity in farmed fish presenting ulcers and the geographical distribution of the pathogens should provide important insights needed to strengthen preventive actions. In this study, we investigated the diversity of Tenacibaculum strains isolated in 28 outbreaks that occurred in Norwegian fish farms in the period 2017–2020. We found that 95% of the 66 strains isolated and characterized, using an existing MultiLocus Sequence Typing system, have not previously been identified, confirming the high diversity of this genus of bacteria in Norway. Several of these Tenacibaculum species seem to be present within restricted areas (e.g., Tenacibaculum dicentrarchi in western Norway), but phylogenetic analysis reveals that several of the strains responsible of ulcerative outbreaks were isolated from different localities (e.g., ST- 172 isolated from northern to southern parts of Norway) and/or from different hosts. Understanding their reservoirs and transmission pathways could help to address major challenges in connection with prophylactic measures and development of vaccines.

Recent Advances in the Race to Design a Rapid Diagnostic Test for Antimicrobial Resistance

Even with advances in antibiotic therapies, bacterial infections persistently plague society and have amounted to one of the most prevalent issues in healthcare today. Moreover, the improper and excessive administration of antibiotics has led to resistance of many pathogens to prescribed therapies, rendering such antibiotics ineffective against infections. While the identification and detection of bacteria in a patient's sample is critical for point-of-care diagnostics and in a clinical setting, the consequent determination of the correct antibiotic for a patient-tailored therapy is equally crucial. As a result, many recent research efforts have been focused on the development of sensors and systems that correctly guide a physician to the best antibiotic to prescribe for an infection, which can in turn, significantly reduce the instances of antibiotic resistance and the evolution of bacteria "superbugs." This review details the advantages and shortcomings of the recent advances (focusing from 2016 and onward) made in the developments of antimicrobial susceptibility testing (AST) measurements. Detection of antibiotic resistance by genomic AST techniques relies on the prediction of antibiotic resistance via extracted bacterial DNA content, while phenotypic determinations typically track physiological changes in cells and/or populations exposed to antibiotics. Regardless of the method used for AST, factors such as cost, scalability, and assay time need to be weighed into their design. With all of the expansive innovation in the field, which technology and sensing systems demonstrate the potential to detect antimicrobial resistance in a clinical setting?

Evaluation of Well Designs to Improve Access to Safe and Clean Water in Rural Tanzania

The objective of this study was to examine three well designs: drilled wells (20–30 m deep), closed dug wells (>5 m deep), and hand-dug open wells (<5 m deep), to determine the water quality for improving access to safe and clean water in rural communities. Heterotrophic plate count (HPC), total coliforms (TC), Escherichia coli (E. coli) and turbidity, were used to assess the water quality of 97 wells. Additionally, the study looked at the microflora diversity of the water, focusing on potential pathogens using outgrowth, PCR, and genome sequencing for 10 wells. Concentrations of TC for the open dug wells (4 × 10⁴ CFU/100 mL) were higher than the drilled (2 × 10³ CFU/100 mL) and closed dug wells (3 × 10³ CFU/100 mL). E. coli concentration for drilled and closed dug wells was <22 MPN (most probable number)/100 mL, but higher for open wells (>154 MPN/100 mL). The drilled well turbidity (11 NTU) was within the standard deviation of the closed well (28 NTU) compared to open dug wells (49 NTU). Drilled and closed wells had similar microbial diversity. There were no significant differences between drilled and closed dug wells. The covering and lining of hand-dug wells should be considered as an alternative to improve access to safe and clean water in rural communities.