Quantifying element incorporation in multispecies biofilms using nanoscale secondary ion mass spectrometry image analysis

Phagocytosis in Marine Coccolithophore Gephyrocapsa huxleyi: Comparison between Calcified and Non-Calcified Strains

Coccolithophores play a significant role in marine calcium carbonate production and carbon cycles, attributing to their unique feature of producing calcareous plates, coccoliths. Coccolithophores also possess a haplo-diplontic life cycle, presenting distinct morphology types and calcification states. However, differences in nutrient acquisition strategies and mixotrophic behaviors of the two life phases remain unclear. In this study, we conducted a series of phagocytosis experiments of calcified diploid and non-calcified haploid strains of coccolithophore Gephyrocapsa huxleyi under light and dark conditions. The phagocytosis capability of each strain was examined based on characteristic fluorescent signals from ingested beads using flow cytometry and fluorescence microscopy. The results show a significantly higher phagocytosis percentage on fluorescent beads in the bacterial prey surrogates of the non-calcified haploid Gephyrocapsa huxleyi strain, than the calcified diploid strain with or without light. In addition, the non-calcified diploid cells seemingly to presented a much higher phagocytosis percentage in darkness than under light. The differential phagocytosis capacities between the calcified diploid and non-calcified haploid Gephyrocapsa huxleyi strains indicate potential distinct nutritional strategies at different coccolithophore life and calcifying stages, which may further shed light on the potential strategies that coccolithophore possesses in unfavorable environments such as twilight zones and the expanding coccolithophore niches in the natural marine environment under the climate change scenario.

Metabolic insights from mass spectrometry imaging of biofilms: A perspective from model microorganisms

Biofilms are dense aggregates of bacterial colonies embedded inside a self-produced polymeric matrix. Biofilms have received increasing attention in medical, industrial, and environmental settings due to their enhanced survival. Their characterization using microscopy techniques has revealed the presence of structural and cellular heterogeneity in many bacterial systems. However, these techniques provide limited chemical detail and lack information about the molecules important for bacterial communication and virulence. Mass spectrometry imaging (MSI) bridges the gap by generating spatial chemical information with unmatched chemical detail, making it an irreplaceable analytical platform in the multi-modal imaging of biofilms. In the last two decades, over 30 species of biofilm-forming bacteria have been studied using MSI in different environments. The literature conveys both analytical advancements and an improved understanding of the effects of environmental variables such as host surface characteristics, antibiotics, and other species of microorganisms on biofilms. This review summarizes the insights from frequently studied model microorganisms. We share a detailed list of organism-wide metabolites, commonly observed mass spectral adducts, culture conditions, strains of bacteria, substrate, broad problem definition, and details of the MS instrumentation, such as ionization sources and matrix, to facilitate future studies. We also compared the spatial characteristics of the secretome under different study designs to highlight changes because of various environmental influences. In addition, we highlight the current limitations of MSI in relation to biofilm characterization to enable cross-comparison between experiments. Overall, MSI has emerged to become an important approach for the spatial/chemical characterization of bacterial biofilms and its use will continue to grow as MSI becomes more accessible.

Microbial Diversity and Activity of Biofilms from Geothermal Springs in Croatia

Hot spring biofilms are stable, highly complex microbial structures. They form at dynamic redox and light gradients and are composed of microorganisms adapted to the extreme temperatures and fluctuating geochemical conditions of geothermal environments. In Croatia, a large number of poorly investigated geothermal springs host biofilm communities. Here, we investigated the microbial community composition of biofilms collected over several seasons at 12 geothermal springs and wells. We found biofilm microbial communities to be temporally stable and highly dominated by Cyanobacteria in all but one high-temperature sampling site (Bizovac well). Of the physiochemical parameters recorded, temperature had the strongest influence on biofilm microbial community composition. Besides Cyanobacteria, the biofilms were mainly inhabited by Chloroflexota, Gammaproteobacteria, and Bacteroidota. In a series of incubations with Cyanobacteria-dominated biofilms from Tuhelj spring and Chloroflexota- and Pseudomonadota-dominated biofilms from Bizovac well, we stimulated either chemoorganotrophic or chemolithotrophic community members, to determine the fraction of microorganisms dependent on organic carbon (in situ predominantly produced via photosynthesis) versus energy derived from geochemical redox gradients (here simulated by addition of thiosulfate). We found surprisingly similar levels of activity in response to all substrates in these two distinct biofilm communities, and observed microbial community composition and hot spring geochemistry to be poor predictors of microbial activity in the study systems.

Emerging Computational Methods in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

The Exploration of Microbial Natural Products and Metabolic Interaction Guided by Mass Spectrometry Imaging

As an impressive mass spectrometry technology, mass spectrometric imaging (MSI) can provide mass spectra data and spatial distribution of analytes simultaneously. MSI has been widely used in diverse fields such as clinical diagnosis, the pharmaceutical industry and environmental study due to its accuracy, high resolution and developing reproducibility. Natural products (NPs) have been a critical source of leading drugs; almost half of marketed drugs are derived from NPs or their derivatives. The continuous search for bioactive NPs from microorganisms or microbiomes has always been attractive. MSI allows us to analyze and characterize NPs directly in monocultured microorganisms or a microbial community. In this review, we briefly introduce current mainstream ionization technologies for microbial samples and the key issue of sample preparation, and then summarize some applications of MSI in the exploration of microbial NPs and metabolic interaction, especially NPs from marine microbes. Additionally, remaining challenges and future prospects are discussed.

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling-an approach we refer to as nanoSIP-nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using ¹⁵N and ¹³C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and 'omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

Pathogens electrogenicity as a tool for in-situ metabolic activity monitoring and drug assessment in biofilms

Concerns regarding increased antibiotic resistance arising from the emergent properties of biofilms have spurred interest in the discovery of novel antibiotic agents and techniques to directly estimate metabolic activity in biofilms. Although a number of methods have been developed to quantify biofilm formation, real-time quantitative assessment of metabolic activity in label-free biofilms remains a challenge. Production of electrical current via extracellular electron transport (EET) has recently been found in pathogens and appears to correlate with their metabolic activity. Accordingly, monitoring the production of electrical currents as an indicator of cellular metabolic activity in biofilms represents a new direction for research aiming to assess and screen the effects of antimicrobials on biofilm activity. In this article, we reviewed EET-capable pathogens and the methods to monitor biofilm activity to discuss advantages of using the capability of pathogens to produce electrical currents and effective combination of these methods. Moreover, we discussed EET mechanisms by pathogenic and environmental bacteria and open questions for the physiological roles of EET in pathogen's biofilm. The present limitations and possible future directions of in situ biofilm metabolic activity assessment for large-scale screening of antimicrobials are also discussed.

Scanning electrochemical microscopy and its potential for studying biofilms and antimicrobial coatings

Biofilms are known to be well-organized microbial communities embedded in an extracellular polymeric matrix, which supplies bacterial protection against external stressors. Biofilms are widespread and diverse, and despite the considerable large number of publications and efforts reported regarding composition, structure and cell-to-cell communication within biofilms in the last decades, the mechanisms of biofilm formation, the interaction and communication between bacteria are still not fully understood. This knowledge is required to understand why biofilms form and how we can combat them or how we can take advantage of these sessile communities, e.g. in biofuel cells. Therefore, in situ and real-time monitoring of nutrients, metabolites and quorum sensing molecules is of high importance, which may help to fill that knowledge gap. This review focuses on the potential of scanning electrochemical microscopy (SECM) as a versatile method for in situ studies providing temporal and lateral resolution in order to elucidate cell-to-cell communication, microbial metabolism and antimicrobial impact, e.g. of antimicrobial coatings through the study of electrochemical active molecules. Given the complexity and diversity of biofilms, challenges and limitations will be also discussed.

Nitrogen Source Governs Community Carbon Metabolism in a Model Hypersaline Benthic Phototrophic Biofilm

Increasing anthropogenic inputs of fixed nitrogen are leading to greater eutrophication of aquatic environments, but it is unclear how this impacts the flux and fate of carbon in lacustrine and riverine systems. Here, we present evidence that the form of nitrogen governs the partitioning of carbon among members in a genome-sequenced, model phototrophic biofilm of 20 members. Consumption of NO₃ ^- as the sole nitrogen source unexpectedly resulted in more rapid transfer of carbon to heterotrophs than when NH₄ ⁺ was also provided, suggesting alterations in the form of carbon exchanged. The form of nitrogen dramatically impacted net community nitrogen, but not carbon, uptake rates. Furthermore, this alteration in nitrogen form caused very large but focused alterations to community structure, strongly impacting the abundance of only two species within the biofilm and modestly impacting a third member species. Our data suggest that nitrogen metabolism may coordinate coupled carbon-nitrogen biogeochemical cycling in benthic biofilms and, potentially, in phototroph-heterotroph consortia more broadly. It further indicates that the form of nitrogen inputs may significantly impact the contribution of these communities to carbon partitioning across the terrestrial-aquatic interface.IMPORTANCE Anthropogenic inputs of nitrogen into aquatic ecosystems, and especially those of agricultural origin, involve a mix of chemical species. Although it is well-known in general that nitrogen eutrophication markedly influences the metabolism of aquatic phototrophic communities, relatively little is known regarding whether the specific chemical form of nitrogen inputs matter. Our data suggest that the nitrogen form alters the rate of nitrogen uptake significantly, whereas corresponding alterations in carbon uptake were minor. However, differences imposed by uptake of divergent nitrogen forms may result in alterations among phototroph-heterotroph interactions that rewire community metabolism. Furthermore, our data hint that availability of other nutrients (i.e., iron) might mediate the linkage between carbon and nitrogen cycling in these communities. Taken together, our data suggest that different nitrogen forms should be examined for divergent impacts on phototrophic communities in fluvial systems and that these anthropogenic nitrogen inputs may significantly differ in their ultimate biogeochemical impacts.

Advances in monitoring soil microbial community dynamic and function

Microorganisms are vital to the overall ecosystem functioning, stability, and sustainability. Soil fertility and health depend on chemical composition and also on the qualitative and quantitative nature of microorganisms inhabiting it. Historically, denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE), single-strand conformation polymorphism, DNA amplification fingerprinting, amplified ribosomal DNA restriction analysis, terminal restriction fragment length polymorphism, length heterogeneity PCR, and ribosomal intergenic spacer analysis were used to assess soil microbial community structure (SMCS), abundance, and diversity. However, these methods had significant shortcomings and limitations for application in land reclamation monitoring. SMCS has been primarily determined by phospholipid fatty acid (PLFA) analysis. This method provides a direct measure of viable biomass in addition to a biochemical profile of the microbial community. PLFA has limitations such as overlap in the composition of microorganisms and the specificity of PLFAs signature. In recent years, high-throughput next-generation sequencing has dramatically increased the resolution and detectable spectrum of diverse microbial phylotypes from environmental samples and it plays a significant role in microbial ecology studies. Next-generation sequencings using 454, Illumina, SOLiD, and Ion Torrent platforms are rapid and flexible. The two methods, PLFA and next-generation sequencing, are useful in detecting changes in microbial community diversity and structure in different ecosystems. Single-molecule real-time (SMRT) and nanopore sequencing technologies represent third-generation sequencing (TGS) platforms that have been developed to address the shortcomings of second-generation sequencing (SGS). Enzymatic and soil respiration analyses are performed to further determine soil quality and microbial activities. Other valuable methods that are being recently applied to microbial function and structures include NanoSIM, GeoChip, and DNA stable staple isotope probing (DNA-SIP) technologies. They are powerful metagenomics tool for analyzing microbial communities, including their structure, metabolic potential, diversity, and their impact on ecosystem functions. This review is a critical analysis of current methods used in monitoring soil microbial community dynamic and functions.

Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data

Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perception of scientific data by as many viewers as possible. We developed a Python module, cmaputil, to create CVD-optimized colormaps, which imports colormaps and modifies them to be perceptually uniform in CVD-safe colorspace while linearizing and maximizing the brightness range. The module is made available to the science community to enable others to easily create their own CVD-optimized colormaps. Here, we present an example CVD-optimized colormap created with this module that is optimized for viewing by those without a CVD as well as those with red-green colorblindness. This colormap, cividis, enables nearly-identical visual-data interpretation to both groups, is perceptually uniform in hue and brightness, and increases in brightness linearly.

NanoSIMS for biological applications: Current practices and analyses

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, the authors provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analyses, and current outlooks. Specifically, the authors offer an overview of SIMS and development of the NanoSIMS. The authors describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includes an in-depth discussion of appropriate colormaps. Additionally, the authors provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Finally, the authors present a perspective on the future of this technology and where they think it will have the greatest impact in near future.