Quantification of uncultured microorganisms by fluorescence microscopy and digital image analysis

Integument colour change: Tracking delayed growth of Oppia nitens as a sub-lethal indicator of soil toxicity

Growth is an important toxicity end-point in ecotoxicology but is rarely used in soil ecotoxicological studies. Here, we assessed the growth change of Oppia nitens when exposed to reference and heavy metal toxicants. To assess mite growth, we developed an image analysis methodology to measure colour spectrum changes of the mite integument at the final developmental stage, as a proxy for growth change. We linked the values of red, green, blue, key-black, and light colour of mites to different growth stages. Based on this concept, we assessed the growth change of mites exposed to cadmium, copper, zinc, lead, boric acid, or phenanthrene at sublethal concentrations in LUFA 2.2 soil for 14 days. Sublethal effects were detected after 7 days of exposure. The growth of O. nitens was more sensitive than survival and reproduction when exposed to copper (EC50growth = 1360 mg/kg compared to EC50reproduction = 2896 mg/kg). Mite growth sensitivity was within the same order of magnitude to mite reproduction when exposed to zinc (EC50growth = 1785; EC50reproduction = 1562 mg/kg). At least 25% of sublethal effects of boric acid and phenanthrene were detected in the mites but growth was not impacted when O. nitens were exposed to lead. Consistent with previous studies, cadmium was the most toxic metal to O. nitens. The mite growth pattern was comparable to mite survival and reproduction from previous studies. Mite growth is a sensitive toxicity endpoint, ecologically relevant, fast, easy to detect, and can be assessed in a non-invasive fashion, thereby complimenting existing O. nitens testing protocols.

Biofilms and Benign Colonic Diseases

The colon has a very large surface area that is covered by a dense mucus layer. The biomass in the colon includes 500-1000 bacterial species at concentrations of ~10¹² colony-forming units per gram of feces. The intestinal epithelial cells and the commensal bacteria in the colon have a symbiotic relationship that results in nutritional support for the epithelial cells by the bacteria and maintenance of the optimal commensal bacterial population by colonic host defenses. Bacteria can form biofilms in the colon, but the exact frequency is uncertain because routine methods to undertake colonoscopy (i.e., bowel preparation) may dislodge these biofilms. Bacteria in biofilms represent a complex community that includes living and dead bacteria and an extracellular matrix composed of polysaccharides, proteins, DNA, and exogenous debris in the colon. The formation of biofilms occurs in benign colonic diseases, such as inflammatory bowel disease and irritable bowel syndrome. The development of a biofilm might serve as a marker for ongoing colonic inflammation. Alternatively, the development of biofilms could contribute to the pathogenesis of these disorders by providing sanctuaries for pathogenic bacteria and reducing the commensal bacterial population. Therapeutic approaches to patients with benign colonic diseases could include the elimination of biofilms and restoration of normal commensal bacteria populations. However, these studies will be extremely difficult unless investigators can develop noninvasive methods for measuring and identifying biofilms. These methods that might include the measurement of quorum sensing molecules, measurement of bile acids, and identification of bacteria uniquely associated with biofilms in the colon.

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

With the acceleration of urbanization and living standards, microorganisms play an increasingly important role in industrial production, bio-technique, and food safety testing. Microorganism biovolume measurements are one of the essential parts of microbial analysis. However, traditional manual measurement methods are time-consuming and challenging to measure the characteristics precisely. With the development of digital image processing techniques, the characteristics of the microbial population can be detected and quantified. The applications of the microorganism biovolume measurement method have developed since the 1980s. More than 62 articles are reviewed in this study, and the articles are grouped by digital image analysis methods with time. This study has high research significance and application value, which can be referred to as microbial researchers to comprehensively understand microorganism biovolume measurements using digital image analysis methods and potential applications.

Direct visualization of living bacterial genotypes using CRISPR/Cas12a-circular reporter nanoprobes

Bacterial genotyping is important for understanding the complex microbiota. Although fluorescence in situ hybridization (FISH) has enabled bacterial community identification with high spatial resolution, its unavoidable cell fixation steps and signal generation by multi-probe stacking greatly limit its application in living bacterial genotyping. Here, we designed polyethyleneimine-encapsulated CRISPR/Cas12a-circular reporter nanoprobes (CasCLR) for rapid and sensitive visualization of gene information in living bacteria. We found that, nanoprobe-based sequential delivery of Cas12a/crRNA and circular reporter into bacteria allowed single genomic loci to initiate trans-cleavage activity of Cas12a, thereby cleaving CLR to generate amplified fluorescent signals for imaging of target gene. Using CasCLR, we can sensitively analyze the percentage of target bacteria in co-culture experiments and directly detect pathogenic bacteria in uncultured mouse gut microbe. In addition, CasCLR has the ability to sensitively analyze specific genotype of microbial communities in vivo. This nanobiotechnology-based bacterial gene analysis is expected to advance understanding of in vivo bacterial cytogenetic information.

Current Techniques to Study Beneficial Plant-Microbe Interactions

Many different experimental approaches have been applied to elaborate and study the beneficial interactions between soil bacteria and plants. Some of these methods focus on changes to the plant and others are directed towards assessing the physiology and biochemistry of the beneficial plant growth-promoting bacteria (PGPB). Here, we provide an overview of some of the current techniques that have been employed to study the interaction of plants with PGPB. These techniques include the study of plant microbiomes; the use of DNA genome sequencing to understand the genes encoded by PGPB; the use of transcriptomics, proteomics, and metabolomics to study PGPB and plant gene expression; genome editing of PGPB; encapsulation of PGPB inoculants prior to their use to treat plants; imaging of plants and PGPB; PGPB nitrogenase assays; and the use of specialized growth chambers for growing and monitoring bacterially treated plants.

Universal activity-based labeling method for ammonia- and alkane-oxidizing bacteria

The advance of metagenomics in combination with intricate cultivation approaches has facilitated the discovery of novel ammonia-, methane-, and other short-chain alkane-oxidizing microorganisms, indicating that our understanding of the microbial biodiversity within the biogeochemical nitrogen and carbon cycles still is incomplete. The in situ detection and phylogenetic identification of novel ammonia- and alkane-oxidizing bacteria remain challenging due to their naturally low abundances and difficulties in obtaining new isolates from complex samples. Here, we describe an activity-based protein profiling protocol allowing cultivation-independent unveiling of ammonia- and alkane-oxidizing bacteria. In this protocol, 1,7-octadiyne is used as a bifunctional enzyme probe that, in combination with a highly specific alkyne-azide cycloaddition reaction, enables the fluorescent or biotin labeling of cells harboring active ammonia and alkane monooxygenases. Biotinylation of these enzymes in combination with immunogold labeling revealed the subcellular localization of the tagged proteins, which corroborated expected enzyme targets in model strains. In addition, fluorescent labeling of cells harboring active ammonia or alkane monooxygenases provided a direct link of these functional lifestyles to phylogenetic identification when combined with fluorescence in situ hybridization. Furthermore, we show that this activity-based labeling protocol can be successfully coupled with fluorescence-activated cell sorting for the enrichment of nitrifiers and alkane-oxidizing bacteria from complex environmental samples, enabling the recovery of high-quality metagenome-assembled genomes. In conclusion, this study demonstrates a novel, functional tagging technique for the reliable detection, identification, and enrichment of ammonia- and alkane-oxidizing bacteria present in complex microbial communities.

The Two Weapons against Bacterial Biofilms: Detection and Treatment

Bacterial biofilms are defined as complex aggregates of bacteria that grow attached to surfaces or are associated with interfaces. Bacteria within biofilms are embedded in a self-produced extracellular matrix made of polysaccharides, nucleic acids, and proteins. It is recognized that bacterial biofilms are responsible for the majority of microbial infections that occur in the human body, and that biofilm-related infections are extremely difficult to treat. This is related with the fact that microbial cells in biofilms exhibit increased resistance levels to antibiotics in comparison with planktonic (free-floating) cells. In the last years, the introduction into the market of novel compounds that can overcome the resistance to antimicrobial agents associated with biofilm infection has slowed down. If this situation is not altered, millions of lives are at risk, and this will also strongly affect the world economy. As such, research into the identification and eradication of biofilms is important for the future of human health. In this sense, this article provides an overview of techniques developed to detect and imaging biofilms as well as recent strategies that can be applied to treat biofilms during the several biofilm formation steps.

Optimizing the hybridization chain reaction-fluorescence in situ hybridization (HCR-FISH) protocol for detection of microbes in sediments

Fluorescence in situ hybridization (FISH) is a canonical tool commonly used in environmental microbiology research to visualize targeted cells. However, the problems of low signal intensity and false-positive signals impede its widespread application. Alternatively, the signal intensity can be amplified by incorporating Hybridization Chain Reaction (HCR) with FISH, while the specificity can be improved through protocol modification and proper counterstaining. Here we optimized the HCR-FISH protocol for studying microbes in environmental samples, particularly marine sediments. Firstly, five sets of HCR initiator/amplifier pairs were tested on the laboratory-cultured bacterium Escherichia coli and the archaeon Methanococcoides methylutens, and two sets displayed high hybridization efficiency and specificity. Secondly, we tried to find the best combination of sample pretreatment methods and HCR-FISH protocol for environmental sample analysis with the aim of producing less false positive signals. Various detachment methods, extraction methods and formulas of hybridization buffer were tested using sediment samples. Thirdly, an image processing method was developed to enhance the DAPI signal of microbial cells against that of abiotic particles, providing a reliable reference for FISH imaging. In summary, our optimized HCR-FISH protocol showed promise to serve as an addendum to traditional FISH for research on environmental microbes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-021-00098-8.

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.

Enrichment and physiological characterization of a novel comammox Nitrospira indicates ammonium inhibition of complete nitrification

The recent discovery of bacteria within the genus Nitrospira capable of complete ammonia oxidation (comammox) demonstrated that the sequential oxidation of ammonia to nitrate via nitrite can also be performed within a single bacterial cell. Although comammox Nitrospira exhibit a wide distribution in natural and engineered ecosystems, information on their physiological properties is scarce due to the limited number of cultured representatives. Additionally, most available genomic information is derived from metagenomic sequencing and high-quality genomes of Nitrospira in general are limited. In this study, we obtained a high (90%) enrichment of a novel comammox species, tentatively named "Candidatus Nitrospira kreftii", and performed a detailed genomic and physiological characterization. The complete genome of "Ca. N. kreftii" allowed reconstruction of its basic metabolic traits. Similar to Nitrospira inopinata, the enrichment culture exhibited a very high ammonia affinity (K_{m(app)_NH3} ≈ 0.040 ± 0.01 µM), but a higher nitrite affinity (K_{m(app)_NO2}- = 12.5 ± 4.0 µM), indicating an adaptation to highly oligotrophic environments. Furthermore, we observed partial inhibition of ammonia oxidation at ammonium concentrations as low as 25 µM. This inhibition of "Ca. N. kreftii" indicates that differences in ammonium tolerance rather than affinity could potentially be a niche determining factor for different comammox Nitrospira.

A refined set of rRNA-targeted oligonucleotide probes for in situ detection and quantification of ammonia-oxidizing bacteria

Ammonia-oxidizing bacteria (AOB) of the betaproteobacterial genera Nitrosomonas and Nitrosospira are key nitrifying microorganisms in many natural and engineered ecosystems. Since many AOB remain uncultured, fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes has been one of the most widely used approaches to study the community composition, abundance, and other features of AOB directly in environmental samples. However, the established and widely used AOB-specific 16S rRNA-targeted FISH probes were designed up to two decades ago, based on much smaller rRNA gene sequence datasets than available today. Several of these probes cover their target AOB lineages incompletely and suffer from a weak target specificity, which causes cross-hybridization of probes that should detect different AOB lineages. Here, a set of new highly specific 16S rRNA-targeted oligonucleotide probes was developed and experimentally evaluated that complements the existing probes and enables the specific detection and differentiation of the known, major phylogenetic clusters of betaproteobacterial AOB. The new probes were successfully applied to visualize and quantify AOB in activated sludge and biofilm samples from seven pilot- and full-scale wastewater treatment systems. Based on its improved target group coverage and specificity, the refined probe set will facilitate future in situ analyses of AOB.

Microbial community analysis using high-throughput sequencing technology: a beginner's guide for microbiologists

Microbial communities present in diverse environments from deep seas to human body niches play significant roles in the complex ecosystem and human health. Characterizing their structural and functional diversities is indispensable, and many approaches, such as microscopic observation, DNA fingerprinting, and PCR-based marker gene analysis, have been successfully applied to identify microorganisms. Since the revolutionary improvement of DNA sequencing technologies, direct and high-throughput analysis of genomic DNA from a whole environmental community without prior cultivation has become the mainstream approach, overcoming the constraints of the classical approaches. Here, we first briefly review the history of environmental DNA analysis applications with a focus on profiling the taxonomic composition and functional potentials of microbial communities. To this end, we aim to introduce the shotgun metagenomic sequencing (SMS) approach, which is used for the untargeted ("shotgun") sequencing of all ("meta") microbial genomes ("genomic") present in a sample. SMS data analyses are performed in silico using various software programs; however, in silico analysis is typically regarded as a burden on wet-lab experimental microbiologists. Therefore, in this review, we present microbiologists who are unfamiliar with in silico analyses with a basic and practical SMS data analysis protocol. This protocol covers all the bioinformatics processes of the SMS analysis in terms of data preprocessing, taxonomic profiling, functional annotation, and visualization.

Development and validation of an alternative parameter for quantification of signals emitted by fluorescently labelled bacteria in microscopic images

In this study, an alternative parameter for quantifying the signals of fluorescently labelled bacteria (e.g. propidium iodide, Cyanine 3, etc.) in microscopic images was investigated. Three common parameters (mean grey value (MGV), mean grey value which is corrected for the background (MGVcwB) and the signal to background ratio (SBR) per bacterial cell) are used as reference parameters. As an alternative, the coefficient of variation (CV) is defined as the ratio of the logarithm of the standard deviation and the logarithm of the mean grey value of a bacterial cell in a microscopic image. The actual fluorescence value was safeguarded by measuring commercially available fluorescence latex microspheres at regular time intervals within our study. The precision and the correlation of the respective values of MGV, MGVcwB, SBR and CV taken from identical images were measured and subsequently normalized in order to enhance the inter-parameter comparability. The average precision of CV was the highest (89% ± 14) with decreasing numbers for MGVcwB, SBR, and MGV (78% ± 25, 71% ± 32, and, 52% ± 22, respectively). Changes in operational parameters, e.g., microscope settings, protocol steps, etc., yielded good results for the CV but less precise results for MGV, MGVcwB, and SBR in the analyses of identical images. In conclusion, using the alternative parameter CV, changes in the composition of microbial ecosystems may thus be investigated at the highest precision level.

A Multicolor Fluorescence in situ Hybridization Approach Using an Extended Set of Fluorophores to Visualize Microorganisms

Fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes is a key method for the detection of (uncultured) microorganisms in environmental and medical samples. A major limitation of standard FISH protocols, however, is the small number of phylogenetically distinct target organisms that can be detected simultaneously. In this study, we introduce a multicolor FISH approach that uses eight fluorophores with distinct spectral properties, which can unambiguously be distinguished by confocal laser scanning microscopy combined with white light laser technology. Hybridization of rRNA-targeted DNA oligonucleotide probes, which were mono-labeled with these fluorophores, to Escherichia coli cultures confirmed that the fluorophores did not affect probe melting behavior. Application of the new multicolor FISH method enabled the differentiation of seven (potentially up to eight) phylogenetically distinct microbial populations in an artificial community of mixed pure cultures (five bacteria, one archaeon, and one yeast strain) and in activated sludge from a full-scale wastewater treatment plant. In contrast to previously published multicolor FISH approaches, this method does not rely on combinatorial labeling of the same microorganisms with different fluorophores, which is prone to biases. Furthermore, images acquired by this method do not require elaborate post-processing prior to analysis. We also demonstrate that the newly developed multicolor FISH method is compatible with an improved cell fixation protocol for FISH targeting Gram-negative bacterial populations. This fixation approach uses agarose embedding during formaldehyde fixation to better preserve the three-dimensional structure of spatially complex samples such as biofilms and activated sludge flocs. The new multicolor FISH approach should be highly suitable for studying structural and functional aspects of microbial communities in virtually all types of samples that can be analyzed by conventional FISH methods.

Advances in Chemical and Biological Methods to Identify Microorganisms-From Past to Present

Fast detection and identification of microorganisms is a challenging and significant feature from industry to medicine. Standard approaches are known to be very time-consuming and labor-intensive (e.g., culture media and biochemical tests). Conversely, screening techniques demand a quick and low-cost grouping of bacterial/fungal isolates and current analysis call for broad reports of microorganisms, involving the application of molecular techniques (e.g., 16S ribosomal RNA gene sequencing based on polymerase chain reaction). The goal of this review is to present the past and the present methods of detection and identification of microorganisms, and to discuss their advantages and their limitations.

Modeling Reveals the Role of Aging and Glucose Uptake Impairment in L1A1 Listeria monocytogenes Biofilm Life Cycle

Listeria monocytogenes is a food-borne pathogen that can persist in food processing plants by forming biofilms on abiotic surfaces. The benefits that bacteria can gain from living in a biofilm, i.e., protection from environmental factors and tolerance to biocides, have been linked to the biofilm structure. Different L. monocytogenes strains build biofilms with diverse structures, and the underlying mechanisms for that diversity are not yet fully known. This work combines quantitative image analysis, cell counts, nutrient uptake data and mathematical modeling to provide a mechanistic insight into the dynamics of the structure of biofilms formed by L. monocytogenes L1A1 (serotype 1/2a) strain. Confocal laser scanning microscopy (CLSM) and quantitative image analysis were used to characterize the structure of L1A1 biofilms throughout time. L1A1 forms flat, thick structures; damaged or dead cells start appearing early in deep layers of the biofilm and rapidly and massively loss biomass after 4 days. We proposed several reaction-diffusion models to explain the system dynamics. Model candidates describe biomass and nutrients evolution including mechanisms of growth and cell spreading, nutrients diffusion and uptake and biofilm decay. Data fitting was used to estimate unknown model parameters and to choose the most appropriate candidate model. Remarkably, standard reaction-diffusion models could not describe the biofilm dynamics. The selected model reveals that biofilm aging and glucose impaired uptake play a critical role in L1A1 L. monocytogenes biofilm life cycle.

More than a decade of experience of landfill leachate treatment with a full-scale anammox plant combining activated sludge and activated carbon biofilm

The performance of biological treatment for high ammonium removal from landfill leachate has been demonstrated. The plant was upgraded combining the activated sludge process followed by activated carbon reactor. Based on a long-term analysis of data collected from 2006 to 2015, the average total nitrogen removal efficiency of 94% was achieved for wastewaters with a C: N ratio varying from 1 to 5 kg-COD kg-TN^-1. But without the presence of activated carbon reactor, the average of biological removal efficiency for total nitrogen was only 82% ± 6% for the activated sludge stage. It means that up to 20% of the nitrogen in the influent can only be eliminated by microorganisms attached to granular activated carbon. After upgrades of the plant, the energy efficiency showed a reduction in the specific energy demand from 1.6 to less than 0.2 kWh m^-3. Methanol consumption and sludge production was reduced by 91% and 96%, respectively. Fluorescent in situ Hybridization was used for microbial diversity analysis on floccular sludge and granular biofilm samples. Anaerobic ammonium oxidation (anammox) bacteria and nitrifiers were detected and Candidatus Scalindua was found in two forms of flocs and biofilms. Due to stochastic risk assessment based on the long-term data analysis given in this research, the treatment criteria were achieved and the combination of granular activated carbon biofilm process and activated sludge can be a novel and sought approach to better enrich anammox biomass for full-scale treatment applications to reduce operating costs and promote nutrient removal stability and efficiency.

Removal of phenol in phenolic resin wastewater by a novel biomaterial: the Phanerochaete chrysosporium pellet containing chlamydospore-like cells

A novel biomaterial, the Phanerochaete chrysosporium pellet (CP) composed of chlamydospore-like cells (CLCs), was prepared and its potential in treating phenolic resin wastewater was evaluated. CP possesses higher phenol removal ability in contrast with mycelial pellets of P. chrysosporium, and CLC can be seen as the naturally immobilized enzymes. At shake-flask level, the ideal pH value, temperature, and inoculation quantity of CP for treatment of 1430 mg/l phenol wastewater were pH 4-6, 30 °C, and 5.0 g/l, respectively, and the maximum specific removal rate, 41.1 mg phenol/g CP/h, was obtained in fixed bed reactor (FBR) when the flow rate of wastewater was 3.4 l/h. During the treatment, FBR harbored amounts of bacteria (135 genera) and eukaryotes, as analyzed by metagenomic sequencing. Bacterial pollution not only decreased reactor performance but also had a negative impact on reusability of CP. Hot water treatment (80-85 °C) is effective to inhibit bacterial pollution, and heat resistance of CLC makes the repeated regrowing of CP be feasible. This work presents an innovative and low-cost biomaterial for phenol removal and will be helpful for the practical application of P. chrysosporium in wastewater treatment.

Complete nitrification by a single microorganism

Nitrification is a two-step process where ammonia is considered to first be oxidized to nitrite by ammonia-oxidizing bacteria (AOB) and/or archaea (AOA), and subsequently to nitrate by nitrite-oxidizing bacteria (NOB). Described by Winogradsky already in 18901, this division of labour between the two functional groups is a generally accepted characteristic of the biogeochemical nitrogen cycle2. Complete oxidation of ammonia to nitrate in one organism (complete ammonia oxidation; comammox) is energetically feasible and it was postulated that this process could occur under conditions selecting for species with lower growth-rates but higher growth-yields than canonical ammonia-oxidizing microorganisms3. Still, organisms catalysing this process have not yet been discovered. Here, we report the enrichment and initial characterization of two Nitrospira species that encode all enzymes necessary for ammonia oxidation via nitrite to nitrate in their genomes, and indeed completely oxidize ammonium to nitrate to conserve energy. Their ammonia monooxygenase (AMO) enzymes are phylogenetically distinct from currently identified AMOs, rendering recent acquisition by horizontal gene transfer from known ammonia-oxidizing microorganisms unlikely. We also found highly similar amoA sequences (encoding the AMO subunit A) in public sequence databases, which were apparently misclassified as methane monooxygenases. This recognition of a novel amoA sequence group will lead to an improved understanding on the environmental abundance and distribution of ammonia-oxidizing microorganisms. Furthermore, the discovery of the long-sought-after comammox process will change our perception of the nitrogen cycle.

Oxygen suppresses light-driven anodic current generation by a mixed phototrophic culture

This paper describes the detrimental effect of photosynthetically evolved oxygen on anodic current generation in the presence of riboflavin upon illumination of a mixed phototrophic culture enriched from a freshwater pond at +0.6 V vs standard hydrogen electrode. In the presence of riboflavin, the phototrophic biomass in the anodic compartment produced an electrical current in response to light/dark cycles (12 h/12 h) over 12 months of operation, generating a maximum current density of 17.5 mA x m(-2) during the dark phase, whereas a much lower current of approximately 2 mA x m(-2) was generated during illumination. We found that the low current generation under light exposure was caused by high rates of reoxidation of reduced riboflavin by oxygen produced during photosynthesis. Quantification of biomass by fluorescence in situ hybridization images suggested that green algae were predominant in both the anode-based biofilm (55.1%) and the anolyte suspension (87.9%) with the remaining biovolume accounted for by bacteria. Genus-level sequencing analysis revealed that bacteria were dominated by cyanobacterium Leptolyngbia (∼35%), while the prevailing algae were Dictyosphaerium, Coelastrum, and Auxenochlorella. This study offers a key comprehension of mediator sensitivity to reoxidation by dissolved oxygen for improvement of microbial solar cell performance.

Accuracy of biovolume formulas for CMEIAS computer-assisted microscopy and body size analysis of morphologically diverse microbial populations and communities

Cell biovolume is a commonly used metric of microbial abundance analyzed by computer-assisted microscopy, but the accuracies of most biovolume formulas have not been validated by ground truth data. We examined the accuracy of 17 biovolume formulas by comparing the computed volumes of 3D models representing 11 microbial morphotypes (cocci, spirals, curved rods, U-shaped rods, regular straight rods, unbranched filaments, ellipsoids, clubs, prosthecates, rudimentary branched rods, and branched filaments) to the volume displacement of the same objects as ground truth. As anticipated, formula accuracy was significantly influenced by the morphotype examined. A few formulas performed very accurately (> 95 %), especially those that adapted to the cell's shape, whereas others were consistently inaccurate or only accurate for one or two morphotypes. As an example of application, indices of morphological diversity in a freshwater biofilm assemblage were shown to be significantly different when microbial abundance among morphotype classes was measured as biovolume body mass rather than cell counts. Spatial analysis of biovolume body mass can also provide insights on the in situ ecophysiological attributes among individuals in microbial populations and communities, including their spatially autocorrelated allometric scaling interrelationships between body size, metabolic activity, resource apportionment and use, food web dynamics, and various cell-cell interactions affecting their growth and colonization behavior within spatially structured biofilm landscapes. This improved computing technology of biovolume algorithms with proven accuracy identifies which formula(s) should be used to compute microbial biovolumes in 2D images of morphologically diverse communities acquired by conventional phase-contrast light microscopy at single-cell resolution.

Nitrotoga-like bacteria are previously unrecognized key nitrite oxidizers in full-scale wastewater treatment plants

Numerous past studies have shown members of the genus Nitrospira to be the predominant nitrite-oxidizing bacteria (NOB) in nitrifying wastewater treatment plants (WWTPs). Only recently, the novel NOB 'Candidatus Nitrotoga arctica' was identified in permafrost soil and a close relative was enriched from activated sludge. Still, little is known about diversity, distribution and functional importance of Nitrotoga in natural and engineered ecosystems. Here we developed Nitrotoga 16S rRNA-specific PCR primers and fluorescence in situ hybridization (FISH) probes, which were applied to screen activated sludge samples from 20 full-scale WWTPs. Nitrotoga-like bacteria were detected by PCR in 11 samples and reached abundances detectable by FISH in seven sludges. They coexisted with Nitrospira in most of these WWTPs, but constituted the only detectable NOB in two systems. Quantitative FISH revealed that Nitrotoga accounted for nearly 2% of the total bacterial community in one of these plants, a number comparable to Nitrospira abundances in other WWTPs. Spatial statistics revealed that Nitrotoga coaggregated with ammonia-oxidizing bacteria, strongly supporting a functional role in nitrite oxidation. This activity was confirmed by FISH in combination with microradiography, which revealed nitrite-dependent autotrophic carbon fixation by Nitrotoga in situ. Correlation of the presence or absence with WWTP operational parameters indicated low temperatures as a main factor supporting high Nitrotoga abundances, although in incubation experiments these NOB remained active over an unexpected range of temperatures, and also at different ambient nitrite concentrations. In conclusion, this study demonstrates that Nitrotoga can be functionally important nitrite oxidizers in WWTPs and can even represent the only known NOB in engineered systems.

Functionally relevant diversity of closely related Nitrospira in activated sludge

Nitrospira are chemolithoautotrophic nitrite-oxidizing bacteria that catalyze the second step of nitrification in most oxic habitats and are important for excess nitrogen removal from sewage in wastewater treatment plants (WWTPs). To date, little is known about their diversity and ecological niche partitioning within complex communities. In this study, the fine-scale community structure and function of Nitrospira was analyzed in two full-scale WWTPs as model ecosystems. In Nitrospira-specific 16S rRNA clone libraries retrieved from each plant, closely related phylogenetic clusters (16S rRNA identities between clusters ranged from 95.8% to 99.6%) within Nitrospira lineages I and II were found. Newly designed probes for fluorescence in situ hybridization (FISH) allowed the specific detection of several of these clusters, whose coexistence in the WWTPs was shown for prolonged periods of several years. In situ ecophysiological analyses based on FISH, relative abundance and spatial arrangement quantification, as well as microautoradiography revealed functional differences of these Nitrospira clusters regarding the preferred nitrite concentration, the utilization of formate as substrate and the spatial coaggregation with ammonia-oxidizing bacteria as symbiotic partners. Amplicon pyrosequencing of the nxrB gene, which encodes subunit beta of nitrite oxidoreductase of Nitrospira, revealed in one of the WWTPs as many as 121 species-level nxrB operational taxonomic units with highly uneven relative abundances in the amplicon library. These results show a previously unrecognized high diversity of Nitrospira in engineered systems, which is at least partially linked to niche differentiation and may have important implications for process stability.

Numerical spatio-temporal characterization of Listeria monocytogenes biofilms

As the structure of biofilms plays a key role in their resistance and persistence, this work presents for the first time the numerical characterization of the temporal evolution of biofilm structures formed by three Listeria monocytogenes strains on two types of stainless-steel supports, AISI 304 SS No. 2B and AISI 316 SS No. 2R. Counting methods, motility tests, fluorescence microscopy and image analysis were combined to study the dynamic evolution of biofilm formation and structure. Image analysis was performed with several well-known parameters as well as a newly defined parameter to quantify spatio-temporal distribution. The results confirm the interstrain variability of L. monocytogenes species regarding biofilm structure and structure evolution. Two types of biofilm were observed: homogeneous or flat and heterogeneous or clustered. Differences in clusters and in attachment and detachment processes were due mainly to the topography and composition of the two surfaces although an effect due to motility was also found.

Role of prokaryotic biomasses and activities in carbon and phosphorus cycles at a coastal, thermohaline front and in offshore waters (Gulf of Manfredonia, Southern Adriatic Sea)

The Western areas of the Adriatic Sea are subjected to inputs of inorganic nutrients and organic matter that can modify the trophic status of the waters and consequently, the microbiological processes involved in the carbon and phosphorus biogeochemical cycles, particularly in shallow coastal environments. To explore this topic, a survey was carried out during the spring of 2003 in a particular hydrodynamic area of the Gulf of Manfredonia, where the potential (P) and real (R) rates of four different microbial exoenzymatic activities (EEA) (α [αG] and ß glucosidases [ßG], leucine aminopeptidase [LAP], and alkaline phosphatase [AP]) as well as the P and R rates of prokaryotic heterotrophic production (PHP), AP as well as the P and R rates of PHP, primary production (PPnet), the prokaryotic and phototrophic stocks and basic hydrological parameters were examined. Three different water masses were found, with a thermohaline front (THF) being detected between the warmer and less saline coastal waters and colder and saltier offshore Adriatic waters. Under the general oligotrophic conditions of the entire Gulf, a decreasing gradient from the coastal toward the offshore areas was detected, with PHP, PPnet, stocks and EEA (αG, ßG, AP) being directly correlated with the temperature and inversely correlated with the salinity, whereas opposite relationships were observed for LAP activity. No enhancement of microbiological activities or stocks was observed at the THF. The use of P or R rates of microbiological activities, which decrease particularly for EEA, could result in discrepancies in interpreting the efficiency of several metabolic processes.

Changing microspatial patterns of sulfate-reducing microorganisms (SRM) during cycling of marine stromatolite mats

Microspatial arrangements of sulfate-reducing microorganisms (SRM) in surface microbial mats (~1.5 mm) forming open marine stromatolites were investigated. Previous research revealed three different mat types associated with these stromatolites, each with a unique petrographic signature. Here we focused on comparing "non-lithifying" (Type-1) and "lithifying" (Type-2) mats. Our results revealed three major trends: (1) Molecular typing using the dsrA probe revealed a shift in the SRM community composition between Type-1 and Type-2 mats. Fluorescence in-situ hybridization (FISH) coupled to confocal scanning-laser microscopy (CSLM)-based image analyses, and 35SO4(2-)-silver foil patterns showed that SRM were present in surfaces of both mat types, but in significantly (p < 0.05) higher abundances in Type-2 mats. Over 85% of SRM cells in the top 0.5 mm of Type-2 mats were contained in a dense 130 µm thick horizontal layer comprised of clusters of varying sizes; (2) Microspatial mapping revealed that locations of SRM and CaCO3 precipitation were significantly correlated (p < 0.05); (3) Extracts from Type-2 mats contained acylhomoserine-lactones (C4- ,C6- ,oxo-C6,C7- ,C8- ,C10- ,C12- , C14-AHLs) involved in cell-cell communication. Similar AHLs were produced by SRM mat-isolates. These trends suggest that development of a microspatially-organized SRM community is closely-associated with the hallmark transition of stromatolite surface mats from a non-lithifying to a lithifying state.

Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review

Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.

New methods for analysis of spatial distribution and coaggregation of microbial populations in complex biofilms

In biofilms, microbial activities form gradients of substrates and electron acceptors, creating a complex landscape of microhabitats, often resulting in structured localization of the microbial populations present. To understand the dynamic interplay between and within these populations, quantitative measurements and statistical analysis of their localization patterns within the biofilms are necessary, and adequate automated tools for such analyses are needed. We have designed and applied new methods for fluorescence in situ hybridization (FISH) and digital image analysis of directionally dependent (anisotropic) multispecies biofilms. A sequential-FISH approach allowed multiple populations to be detected in a biofilm sample. This was combined with an automated tool for vertical-distribution analysis by generating in silico biofilm slices and the recently developed Inflate algorithm for coaggregation analysis of microbial populations in anisotropic biofilms. As a proof of principle, we show distinct stratification patterns of the ammonia oxidizers Nitrosomonas oligotropha subclusters I and II and the nitrite oxidizer Nitrospira sublineage I in three different types of wastewater biofilms, suggesting niche differentiation between the N. oligotropha subclusters, which could explain their coexistence in the same biofilms. Coaggregation analysis showed that N. oligotropha subcluster II aggregated closer to Nitrospira than did N. oligotropha subcluster I in a pilot plant nitrifying trickling filter (NTF) and a moving-bed biofilm reactor (MBBR), but not in a full-scale NTF, indicating important ecophysiological differences between these phylogenetically closely related subclusters. By using high-resolution quantitative methods applicable to any multispecies biofilm in general, the ecological interactions of these complex ecosystems can be understood in more detail.

Depletion of unwanted nucleic acid templates by selective cleavage: LNAzymes, catalytically active oligonucleotides containing locked nucleic acids, open a new window for detecting rare microbial community members

Many studies of molecular microbial ecology rely on the characterization of microbial communities by PCR amplification, cloning, sequencing, and phylogenetic analysis of genes encoding rRNAs or functional marker enzymes. However, if the established clone libraries are dominated by one or a few sequence types, the cloned diversity is difficult to analyze by random clone sequencing. Here we present a novel approach to deplete unwanted sequence types from complex nucleic acid mixtures prior to cloning and downstream analyses. It employs catalytically active oligonucleotides containing locked nucleic acids (LNAzymes) for the specific cleavage of selected RNA targets. When combined with in vitro transcription and reverse transcriptase PCR, this LNAzyme-based technique can be used with DNA or RNA extracts from microbial communities. The simultaneous application of more than one specific LNAzyme allows the concurrent depletion of different sequence types from the same nucleic acid preparation. This new method was evaluated with defined mixtures of cloned 16S rRNA genes and then used to identify accompanying bacteria in an enrichment culture dominated by the nitrite oxidizer "Candidatus Nitrospira defluvii." In silico analysis revealed that the majority of publicly deposited rRNA-targeted oligonucleotide probes may be used as specific LNAzymes with no or only minor sequence modifications. This efficient and cost-effective approach will greatly facilitate tasks such as the identification of microbial symbionts in nucleic acid preparations dominated by plastid or mitochondrial rRNA genes from eukaryotic hosts, the detection of contaminants in microbial cultures, and the analysis of rare organisms in microbial communities of highly uneven composition.

Nitrification expanded: discovery, physiology and genomics of a nitrite-oxidizing bacterium from the phylum Chloroflexi

Nitrite-oxidizing bacteria (NOB) catalyze the second step of nitrification, a major process of the biogeochemical nitrogen cycle, but the recognized diversity of this guild is surprisingly low and only two bacterial phyla contain known NOB. Here, we report on the discovery of a chemolithoautotrophic nitrite oxidizer that belongs to the widespread phylum Chloroflexi not previously known to contain any nitrifying organism. This organism, named Nitrolancetus hollandicus, was isolated from a nitrifying reactor. Its tolerance to a broad temperature range (25–63 °C) and low affinity for nitrite (K_s=1 mℳ), a complex layered cell envelope that stains Gram positive, and uncommon membrane lipids composed of 1,2-diols distinguish N. hollandicus from all other known nitrite oxidizers. N. hollandicus grows on nitrite and CO₂, and is able to use formate as a source of energy and carbon. Genome sequencing and analysis of N. hollandicus revealed the presence of all genes required for CO₂ fixation by the Calvin cycle and a nitrite oxidoreductase (NXR) similar to the NXR forms of the proteobacterial nitrite oxidizers, Nitrobacter and Nitrococcus. Comparative genomic analysis of the nxr loci unexpectedly indicated functionally important lateral gene transfer events between Nitrolancetus and other NOB carrying a cytoplasmic NXR, suggesting that horizontal transfer of the NXR module was a major driver for the spread of the capability to gain energy from nitrite oxidation during bacterial evolution. The surprising discovery of N. hollandicus significantly extends the known diversity of nitrifying organisms and likely will have implications for future research on nitrification in natural and engineered ecosystems.

Peptide nucleic acid fluorescence in situ hybridization for identification of Listeria genus, Listeria monocytogenes and Listeria ivanovii

A fluorescent in situ hybridization (FISH) method in conjunction with fluorescin-labeled peptide nucleic acid (PNA) probes (PNA-FISH) for detection of Listeria species was developed. In silico analysis showed that three PNA probes Lis-16S-1, Lm-16S-2 and Liv-16S-5 were suitable for specific identification of Listeria genus, Listeria monocytogenes and Listeria ivanovii, respectively. These probes were experimentally verified by their reactivity against 19 strains of six Listeria species (excluding newly described species Listeria marthii and Listeria rocourtiae) and eight other bacterial species. The PNA-FISH method was optimized as 30 min of hybridization with 0.2% Triton X-100 in the solution and used to identify 85 Listeria strains from individual putative Listeria colonies on PALCAM agar plates streaked from selectively enriched cultures of 780 food or food-related samples. Of the 85 Listeria strains, thirty-seven were identified as L. monocytogenes with the probe Lm-16S-2 and two as L. ivanovii with the probe Liv-16S-5 which was in agreement with the results obtained by the API LISTERIA method. Thus, the PNA-FISH protocol has the potential for identification of pathogenic Listeria spp. from food or food-related samples.

Enhanced analysis of bacteria susceptibility in connected biofilms

A common method for visualizing bacterial biofilms is through confocal laser scanning microscopy images. Current software packages separate connected-biofilm bacteria from unconnected bacteria, such as planktonic or dispersed bacteria, but do not save both image sequences, making interpretation of the two bacterial populations difficult. Thus we report the development of an algorithm to save separate image sequences and enable qualitative and quantitative evaluation of each bacterial population. To improve bacterial viability assessment using a membrane integrity dye, a colocalization algorithm was also developed. This assigns colocalized pixels to the dead bacteria population, rather than to both the live and dead bacteria groups. Visually, this makes it clearer to distinguish a green live bacteria pixel from a yellow colocalized dead bacteria pixel. This algorithm also aids in the quantification of viability for connected-biofilm bacteria and unconnected bacteria to investigate susceptibility of each population to antimicrobials. The utility of these algorithms was demonstrated with Pseudomonas aeruginosa biofilms treated with ciprofloxacin hydrochloride. Results from this study indicate that quantification with colocalization adjustment can prevent underestimation of dead bacteria. These improvements in image processing will enable researchers to visually differentiate connected-biofilm and unconnected bacteria in a single image and to quantify these populations independently for viability without double counting the colocalized image pixels.

Of microparticles and bacteria identification--(resonance) Raman micro-spectroscopy as a tool for biofilm analysis

Confocal resonance Raman microscopy is a powerful tool for the non-invasive analysis of complex biological aggregates without preparation and prior knowledge of the samples. We present the capabilities of confocal resonance Raman microscopy with a spatial resolution of 350 nm2×2.0 μm and excitation times of 1 s and less per recorded spectrum. Granules sampled from two sequencing batch reactors (SBR) for anaerobic ammonium oxidization (anammox) were regularly mapped in vivo for three months after SBR startup. Uncultured microorganisms and mineral particles were tracked throughout operation and identified in situ by their (resonance) Raman spectra. Co-existing microcolonies of Nitrosomonae formed the outer layer of anammox granules. Polymorph TiO2 microparticles were found embedded in the outer layer of granules overgrown with purple bacteria, indicating bacterial response to the variant toxicity of the mineral phase.

A novel algorithm for the determination of bacterial cell volumes that is unbiased by cell morphology

The determination of cell volumes and biomass offers a means of comparing the standing stocks of auto- and heterotrophic microbes of vastly different sizes for applications including the assessment of the flux of organic carbon within aquatic ecosystems. Conclusions about the importance of particular genotypes within microbial communities (e.g., of filamentous bacteria) may strongly depend on whether their contribution to total abundance or to biomass is regarded. Fluorescence microscopy and image analysis are suitable tools for determining bacterial biomass that moreover hold the potential to replace labor-intensive manual measurements by fully automated approaches. However, the current approaches to calculate bacterial cell volumes from digital images are intrinsically biased by the models that are used to approximate the morphology of the cells. Therefore, we developed a generic contour based algorithm to reconstruct the volumes of prokaryotic cells from two-dimensional representations (i.e., microscopic images) irrespective of their shape. Geometric models of commonly encountered bacterial morphotypes were used to verify the algorithm and to compare its performance with previously described approaches. The algorithm is embedded in a freely available computer program that is able to process both raw (8-bit grayscale) and thresholded (binary) images in a fully automated manner.

In situ techniques and digital image analysis methods for quantifying spatial localization patterns of nitrifiers and other microorganisms in biofilm and flocs

The spatial localization patterns of microorganisms in multispecies biofilms reflect numerous phenomena that influence sessile microbial life, such as substrate concentration gradients within the biofilm and biological interactions with other biofilm populations. Quantitative and population-specific in situ analyses of spatial patterns have a high potential to provide novel insights into the biology of biofilm organisms, including yet uncultured microbes, but such approaches have been developed and used in a few studies only. Here, we outline digital image analysis methods to quantify the coaggregation, mutual avoidance, or random distribution of microbial populations in biofilm and flocs. A protocol is provided for fluorescence in situ hybridization with rRNA-targeted probes, which preserves the three-dimensional biofilm architecture for confocal microscopy and image analysis, and the combined use of these approaches is demonstrated by spatial analyses of nitrifying bacteria in complex biofilm samples.

Discriminating multi-species populations in biofilms with peptide nucleic acid fluorescence in situ hybridization (PNA FISH)

BACKGROUND

Our current understanding of biofilms indicates that these structures are typically composed of many different microbial species. However, the lack of reliable techniques for the discrimination of each population has meant that studies focusing on multi-species biofilms are scarce and typically generate qualitative rather than quantitative data.

METHODOLOGY/PRINCIPAL FINDINGS

We employ peptide nucleic acid fluorescence in situ hybridization (PNA FISH) methods to quantify and visualize mixed biofilm populations. As a case study, we present the characterization of Salmonella enterica/Listeria monocytogenes/Escherichia coli single, dual and tri-species biofilms in seven different support materials. Ex-situ, we were able to monitor quantitatively the populations of ∼56 mixed species biofilms up to 48 h, regardless of the support material. In situ, a correct quantification remained more elusive, but a qualitative understanding of biofilm structure and composition is clearly possible by confocal laser scanning microscopy (CLSM) at least up to 192 h. Combining the data obtained from PNA FISH/CLSM with data from other established techniques and from calculated microbial parameters, we were able to develop a model for this tri-species biofilm. The higher growth rate and exopolymer production ability of E. coli probably led this microorganism to outcompete the other two [average cell numbers (cells/cm(2)) for 48 h biofilm: E. coli 2,1 × 10(8) (± 2,4 × 10(7)); L. monocytogenes 6,8 × 10(7) (± 9,4 × 10(6)); and S. enterica 1,4 × 10(6) (± 4,1 × 10(5))]. This overgrowth was confirmed by CSLM, with two well-defined layers being easily identified: the top one with E. coli, and the bottom one with mixed regions of L. monocytogenes and S. enterica.

SIGNIFICANCE

While PNA FISH has been described previously for the qualitative study of biofilm populations, the present investigation demonstrates that it can also be used for the accurate quantification and spatial distribution of species in polymicrobial communities. Thus, it facilitates the understanding of interspecies interactions and how these are affected by changes in the surrounding environment.

Biofilm image reconstruction for assessing structural parameters

The structure of biofilms can be numerically quantified from microscopy images using structural parameters. These parameters are used in biofilm image analysis to compare biofilms, to monitor temporal variation in biofilm structure, to quantify the effects of antibiotics on biofilm structure and to determine the effects of environmental conditions on biofilm structure. It is often hypothesized that biofilms with similar structural parameter values will have similar structures; however, this hypothesis has never been tested. The main goal was to test the hypothesis that the commonly used structural parameters can characterize the differences or similarities between biofilm structures. To achieve this goal (1) biofilm image reconstruction was developed as a new tool for assessing structural parameters, (2) independent reconstructions using the same starting structural parameters were tested to see how they differed from each other, (3) the effect of the original image parameter values on reconstruction success was evaluated, and (4) the effect of the number and type of the parameters on reconstruction success was evaluated. It was found that two biofilms characterized by identical commonly used structural parameter values may look different, that the number and size of clusters in the original biofilm image affect image reconstruction success and that, in general, a small set of arbitrarily selected parameters may not reveal relevant differences between biofilm structures.