Transcript amplification from single bacterium for transcriptome analysis

Dual spatial host-bacterial gene expression in Mycobacterium abscessus respiratory infections

Co-localization of spatial transcriptome information of host and pathogen can revolutionize our understanding of microbial pathogenesis. Here, we aimed to demonstrate that customized bacterial probes can be successfully used to identify host-pathogen interactions in formalin-fixed-paraffin-embedded (FFPE) tissues by probe-based spatial transcriptomics technology. We analyzed the spatial gene expression of bacterial transcripts with the host transcriptomic profile in murine lung tissue chronically infected with Mycobacterium abscessus embedded in agar beads. Customized mycobacterial probes were designed for the constitutively expressed rpoB gene (an RNA polymerase β subunit) and the virulence factor precursor lsr2, modulated by oxidative stress. We found a correlation between the rpoB expression, bacterial abundance in the airways, and an increased expression of lsr2 virulence factor in lung tissue with high oxidative stress. Overall, we demonstrate the potential of dual bacterial and host gene expression assay in FFPE tissues, paving the way for the simultaneous detection of host and bacterial transcriptomes in pathological tissues.

Highly Multiplexed Spatial Transcriptomics in Bacteria

Single-cell decisions made in complex environments underlie many bacterial phenomena. Image-based transcriptomics approaches offer an avenue to study such behaviors, yet these approaches have been hindered by the massive density of bacterial mRNA. To overcome this challenge, we combine 1000-fold volumetric expansion with multiplexed error robust fluorescence in situ hybridization (MERFISH) to create bacterial-MERFISH. This method enables high-throughput, spatially resolved profiling of thousands of operons within individual bacteria. Using bacterial-MERFISH, we dissect the response of E. coli to carbon starvation, systematically map subcellular RNA organization, and chart the adaptation of a gut commensal B. thetaiotaomicron to micron-scale niches in the mammalian colon. We envision bacterial-MERFISH will be broadly applicable to the study of bacterial single-cell heterogeneity in diverse, spatially structured, and native environments.

The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

Dual RNA-seq in filarial nematodes and Wolbachia endosymbionts using RNase H based ribosomal RNA depletion

Lymphatic filariasis is caused by parasitic nematodes and is a leading cause of disability worldwide. Many filarial worms contain the bacterium Wolbachia as an obligate endosymbiont. RNA sequencing is a common technique used to study their molecular relationships and to identify potential drug targets against the nematode and bacteria. Ribosomal RNA (rRNA) is the most abundant RNA species, accounting for 80-90% of the RNA in a sample. To reduce sequencing costs, it is necessary to remove ribosomal reads through poly-A enrichment or ribosomal depletion. Bacterial RNA does not contain a poly-A tail, making it difficult to sequence both the nematode and Wolbachia from the same library preparation using standard poly-A selection. Ribosomal depletion can utilize species-specific oligonucleotide probes to remove rRNA through pull-down or degradation methods. While species-specific probes are commercially available for many commonly studied model organisms, there are currently limited depletion options for filarial parasites. Here, we performed total RNA sequencing from Brugia malayi containing the Wolbachia symbiont (wBm) and designed ssDNA depletion probes against their rRNA sequences. We compared the total RNA library to poly-A enriched, Terminator 5'-Phosphate-Dependent Exonuclease treated, NEBNext Human/Bacteria rRNA depleted and our custom nematode probe depleted libraries. The custom nematode depletion library had the lowest percentage of ribosomal reads across all methods, with a 300-fold decrease in rRNA when compared to the total RNA library. The nematode depletion libraries also contained the highest percentage of Wolbachia mRNA reads, resulting in a 16-1,000-fold increase in bacterial reads compared to the other enrichment and depletion methods. Finally, we found that the Brugia malayi depletion probes can remove rRNA from the filarial worm Dirofilaria immitis and the majority of rRNA from the more distantly related free living nematode Caenorhabditis elegans. These custom filarial probes will allow for future dual RNA-seq experiments between nematodes and their bacterial symbionts from a single sequencing library.

Single-cell phenotyping of bacteria combined with deep sequencing for improved contextualization of microbiome analyses

Great effort was made to characterize the bacterial communities inhabiting the human body as a factor in disease, resulting in the realization that a wide spectrum of diseases is associated with an altered composition of the microbiome. However, the identification of disease-relevant bacteria has been hindered by the high cross-sectional diversity of individual microbiomes, and in most cases, it remains unclear whether the observed alterations are cause or consequence of disease. Hence, innovative analysis approaches are required that enable inquiries of the microbiome beyond mere taxonomic cataloging. This review highlights the utility of microbiota flow cytometry, a single-cell analysis platform to directly interrogate cellular interactions, cell conditions, and crosstalk with the host's immune system within the microbiome to take into consideration the role of microbes as critical interaction partners of the host and the spectrum of microbiome alterations, beyond compositional changes. In conjunction with advanced sequencing approaches it could reveal the genetic potential of target bacteria and advance our understanding of taxonomic diversity and gene usage in the context of the microenvironment. Single-cell bacterial phenotyping has the potential to change our perspective on the human microbiome and empower microbiome research for the development of microbiome-based therapy approaches and personalized medicine.

Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures

IMPORTANCE

Microbes present one of the most diverse sources of biochemistry in nature, and mRNA sequencing provides a comprehensive view of this biological activity by quantitatively measuring microbial transcriptomes. However, efficient mRNA capture for sequencing presents significant challenges in prokaryotes as mRNAs are not poly-adenylated and typically make up less than 5% of total RNA compared with rRNAs that exceed 80%. Recently developed methods for sequencing bacterial mRNA typically rely on depleting rRNA by tiling large probe sets against rRNAs; however, such approaches are expensive, time-consuming, and challenging to scale to varied bacterial species and complex microbial communities. Therefore, we developed EMBR-seq+, a method that requires fewer than 10 short oligonucleotides per rRNA to achieve up to 99% rRNA depletion in diverse bacterial species. Finally, EMBR-seq+ resulted in a deeper view of the transcriptome, enabling systematic quantification of how microbial interactions result in altering the transcriptional state of bacteria within co-cultures.

Bacterial single-cell transcriptomics: Recent technical advances and future applications in dentistry

Metagenomics and metatranscriptomics have enhanced our understanding of the oral microbiome and its impact on oral health. However, these approaches have inherent limitations in exploring individual cells and the heterogeneity within mixed microbial communities, which restricts our current understanding to bulk cells and species-level information. Fortunately, recent technical advances have enabled the application of single-cell RNA sequencing (scRNA-seq) for studying bacteria, shedding light on cell-to-cell diversity and interactions between host-bacterial cells at the single-cell level. Here, we address the technical barriers in capturing RNA from single bacterial cells and highlight pioneering studies from the past decade. We also discuss recent achievements in host-bacterial dual transcriptional profiling at the single-cell level. Bacterial scRNA-seq provides advantages in various research fields, including the investigation of phenotypic heterogeneity within genetically identical bacteria, identification of rare cell types, detection of antibiotic-resistant or persistent cells, analysis of individual gene expression patterns and metabolic activities, and characterization of specific microbe-host interactions. Integrating single-cell techniques with bulk approaches is essential to gain a comprehensive understanding of oral diseases and develop targeted and personalized treatment in dentistry. The reviewed pioneering studies are expected to inspire future research on the oral microbiome at the single-cell level.

Enhancing the sensitivity of bacterial single-cell RNA sequencing using RamDA-seq and Cas9-based rRNA depletion

Bacterial populations exhibit heterogeneity in gene expression, which facilitates their survival and adaptation to unstable and unpredictable environments through the bet-hedging strategy. However, unraveling the rare subpopulations and heterogeneity in gene expression using population-level gene expression analysis remains a challenging task. Single-cell RNA sequencing (scRNA-seq) has the potential to identify rare subpopulations and capture heterogeneity in bacterial populations, but standard methods for scRNA-seq in bacteria are still under development, mainly due to differences in mRNA abundance and structure between eukaryotic and prokaryotic organisms. In this study, we present a hybrid approach that combines random displacement amplification sequencing (RamDA-seq) with Cas9-based rRNA depletion for scRNA-seq in bacteria. This approach allows cDNA amplification and subsequent sequencing library preparation from low-abundance bacterial RNAs. We evaluated its sequenced read proportion, gene detection sensitivity, and gene expression patterns from the dilution series of total RNA or the sorted single Escherichia coli cells. Our results demonstrated the detection of more than 1000 genes, about 24% of the genes in the E. coli genome, from single cells with less sequencing effort compared to conventional methods. We observed gene expression clusters between different cellular proliferation states or heat shock treatment. The approach demonstrated high detection sensitivity in gene expression analysis compared to current bacterial scRNA-seq methods and proved to be an invaluable tool for understanding the ecology of bacterial populations and capturing the heterogeneity of bacterial gene expression.

Pesticide pestilence: Global scenario and recent advances in detection and degradation methods

Increased anthropogenic activities are confronted as the main cause for rising environmental and health concerns globally, presenting an indisputable threat to both environment and human well-being. Modern-day industrialization has given rise to a cascade of concurrent environmental and health challenges. The global human population is growing at an alarming rate, posing tremendous pressure on future food security, and healthy and environmentally sustainable diets for all. To feed all, the global food production needs to increase by 50% by 2050, but this increase has to occur from the limited arable land, and under the present-day climate variabilities. Pesticides have become an integral component of contemporary agricultural system, safeguarding crops from pests and diseases and their use must be reduce to fulfill the SDG (Sustainable Development Goals) agenda . However, their indiscriminate use, lengthy half-lives, and high persistence in soil and aquatic ecosystems have impacted global sustainability, overshot the planetary boundaries and damaged the pure sources of life with severe and negative impacts on environmental and human health. Here in this review, we have provided an overview of the background of pesticide use and pollution status and action strategies of top pesticide-using nations. Additionally, we have summarized biosensor-based methodologies for the rapid detection of pesticide residue. Finally, omics-based approaches and their role in pesticide mitigation and sustainable development have been discussed qualitatively. The main aim of this review is to provide the scientific facts for pesticide management and application and to provide a clean, green, and sustainable environment for future generations.

Single-cell transcriptomics and data analyses for prokaryotes-Past, present and future concepts

Transcriptomics, or more specifically mRNA sequencing, is a powerful tool to study gene expression at the single-cell level (scRNA-seq) which enables new insights into a plethora of biological processes. While methods for single-cell RNA-seq in eukaryotes are well established, application to prokaryotes is still challenging. Reasons for that are rigid and diverse cell wall structures hampering lysis, the lack of polyadenylated transcripts impeding mRNA enrichment, and minute amounts of RNA requiring amplification steps before sequencing. Despite those obstacles, several promising scRNA-seq approaches for bacteria have been published recently, albeit difficulties in the experimental workflow and data processing and analysis remain. In particular, bias is often introduced by amplification which makes it difficult to distinguish between technical noise and biological variation. Future optimization of experimental procedures and data analysis algorithms are needed for the improvement of scRNA-seq but also to aid in the emergence of prokaryotic single-cell multi-omics. to help address 21st century challenges in the biotechnology and health sector.

Biotechnological tools to elucidate the mechanism of pesticide degradation in the environment

Pesticides are widely used in agriculture, households, and industries; however, they have caused severe negative effects on the environment and human health. To clean up pesticide contaminated sites, various technological strategies, i.e. physicochemical and biological, are currently being used throughout the world. Biological approaches have proven to be a viable method for decontaminating pesticide-contaminated soils and water environments. The biological process eliminates contaminants by utilizing microorganisms' catabolic ability. Pesticide degradation rates are influenced by a variety of factors, including the pesticide's structure, concentration, solubility in water, soil type, land use pattern, and microbial activity in the soil. There is currently a knowledge gap in this field of study because researchers are unable to gather collective information on the factors affecting microbial growth, metabolic pathways, optimal conditions for degradation, and genomic, transcriptomic, and proteomic changes caused by pesticide stress on the microbial communities. The use of advanced tools and omics technology in research can bridge the existing gap in our knowledge regarding the bioremediation of pesticides. This review provides new insights on the research gaps and offers potential solutions for pesticide removal from the environment through the use of various microbe-mediated technologies.

Interfacing microfluidics with information-rich detection systems for cells, bioparticles, and molecules

The development of elegant and numerous microfluidic manipulations has enabled significant advances in the processing of small volume samples and the detection of minute amounts of biomaterials. Effective isolation of single cells in a defined volume as well as manipulations of complex bioparticle or biomolecule mixtures allows for the utilization of information-rich detection methods including mass spectrometry, electron microscopy imaging, and amplification/sequencing. The art and science of translating biosamples from microfluidic platforms to highly advanced, information-rich detection system is the focus of this review, where we term the translation between the microfluidics elements to the external world “off-chipping.” When presented with the challenge of presenting sub-nanoliter volumes of manipulated sample to a detection scheme, several delivery techniques have been developed for effective analysis. These techniques include spraying (electrospray, nano-electrospray, pneumatic), meniscus-defined volumes (droplets, plugs), constrained volumes (narrow channels, containers), and phase changes (deposition, freezing). Each technique has been proven effective in delivering highly defined samples from microfluidic systems to the detection elements. This review organizes and presents selective publications that illustrate the advancements of these delivery techniques with respect to the type of sample analyzed, while introducing each strategy and providing historical perspective. The publications highlighted in this review were chosen due to their significance and relevance in the development of their respective off-chip technique.

Characterization of glyphosate-resistant Burkholderia anthina and Burkholderia cenocepacia isolates from a commercial Roundup® solution

Roundup® is the brand name for herbicide solutions containing glyphosate, which specifically inhibits the 5-enolpyruvyl-shikimate-3-phosphate (EPSP) synthase of the shikimate pathway. The inhibition of the EPSP synthase causes plant death because EPSP is required for biosynthesis of aromatic amino acids. Glyphosate also inhibits the growth of archaea, bacteria, Apicomplexa, algae and fungi possessing an EPSP synthase. Here, we have characterized two glyphosate-resistant bacteria from a Roundup solution. Taxonomic classification revealed that the isolates 1CH1 and 2CH1 are Burkholderia anthina and Burkholderia cenocepacia strains respectively. Both isolates cannot utilize glyphosate as a source of phosphorus and synthesize glyphosate-sensitive EPSP synthase variants. Burkholderia. anthina 1CH1 and B. cenocepacia 2CH1 tolerate high levels of glyphosate because the herbicide is not taken up by the bacteria. Previously, it has been observed that the exposure of soil bacteria to herbicides like glyphosate promotes the development of antibiotic resistances. Antibiotic sensitivity testing revealed that the only the B. cenocepacia 2CH1 isolate showed increased resistance to a variety of antibiotics. Thus, the adaptation of B. anthina 1CH1 and B. cenocepacia 2CH1 to glyphosate did not generally increase the antibiotic resistance of both bacteria. However, our study confirms the genomic adaptability of bacteria belonging to the genus Burkholderia.

mDrop-Seq: Massively Parallel Single-Cell RNA-Seq of Saccharomyces cerevisiae and Candida albicans

Advances in high-throughput single-cell RNA sequencing (scRNA-seq) have been limited by technical challenges such as tough cell walls and low RNA quantity that prevent transcriptomic profiling of microbial species at throughput. We present microbial Drop-seq or mDrop-seq, a high-throughput scRNA-seq technique that is demonstrated on two yeast species, Saccharomyces cerevisiae, a popular model organism, and Candida albicans, a common opportunistic pathogen. We benchmarked mDrop-seq for sensitivity and specificity and used it to profile 35,109 S. cerevisiae cells to detect variation in mRNA levels between them. As a proof of concept, we quantified expression differences in heat shock S. cerevisiae using mDrop-seq. We detected differential activation of stress response genes within a seemingly homogenous population of S. cerevisiae under heat shock. We also applied mDrop-seq to C. albicans cells, a polymorphic and clinically relevant species of yeast with a thicker cell wall compared to S. cerevisiae. Single-cell transcriptomes in 39,705 C. albicans cells were characterized using mDrop-seq under different conditions, including exposure to fluconazole, a common anti-fungal drug. We noted differential regulation in stress response and drug target pathways between C. albicans cells, changes in cell cycle patterns and marked increases in histone activity when treated with fluconazole. We demonstrate mDrop-seq to be an affordable and scalable technique that can quantify the variability in gene expression in different yeast species. We hope that mDrop-seq will lead to a better understanding of genetic variation in pathogens in response to stimuli and find immediate applications in investigating drug resistance, infection outcome and developing new drugs and treatment strategies.

Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters

Antibiotic persistence is a phenomenon in which rare cells of a clonal bacterial population can survive antibiotic doses that kill their kin, even though the entire population is genetically susceptible. With antibiotic treatment failure on the rise, there is growing interest in understanding the molecular mechanisms underlying bacterial phenotypic heterogeneity and antibiotic persistence. However, elucidating these rare cell states can be technically challenging. The advent of single-cell techniques has enabled us to observe and quantitatively investigate individual cells in complex, phenotypically heterogeneous populations. In this review, we will discuss current technologies for studying persister phenotypes, including fluorescent tags and biosensors used to elucidate cellular processes; advances in flow cytometry, mass spectrometry, Raman spectroscopy, and microfluidics that contribute high-throughput and high-content information; and next-generation sequencing for powerful insights into genetic and transcriptomic programs. We will further discuss existing knowledge gaps, cutting-edge technologies that can address them, and how advances in single-cell microbiology can potentially improve infectious disease treatment outcomes.

RiboRid: A low cost, advanced, and ultra-efficient method to remove ribosomal RNA for bacterial transcriptomics

RNA sequencing techniques have enabled the systematic elucidation of gene expression (RNA-Seq), transcription start sites (differential RNA-Seq), transcript 3′ ends (Term-Seq), and post-transcriptional processes (ribosome profiling). The main challenge of transcriptomic studies is to remove ribosomal RNAs (rRNAs), which comprise more than 90% of the total RNA in a cell. Here, we report a low-cost and robust bacterial rRNA depletion method, RiboRid, based on the enzymatic degradation of rRNA by thermostable RNase H. This method implemented experimental considerations to minimize nonspecific degradation of mRNA and is capable of depleting pre-rRNAs that often comprise a large portion of RNA, even after rRNA depletion. We demonstrated the highly efficient removal of rRNA up to a removal efficiency of 99.99% for various transcriptome studies, including RNA-Seq, Term-Seq, and ribosome profiling, with a cost of approximately $10 per sample. This method is expected to be a robust method for large-scale high-throughput bacterial transcriptomic studies.

Removal of ribosomal RNAs, a major constituent (over 90%) of cellular RNA is a critical experimental step for transcriptomic studies that deal with messenger RNAs. In this manuscript, we describe a robust method to subtract ribosomal RNA from various RNA samples. The method is based on the enzymatic degradation of target RNA by short complementary DNA and RNA:DNA duplex specific nuclease. The method comprises carefully designed experimental procedures to minimize experimental bias and unwanted removal of messenger RNAs. We validate the method on various types of transcriptomic studies for seven diverse bacterial species. This method successfully removed ribosomal RNA with over 99% of efficiency and it was comparable to commercial systems even for degraded RNA samples at a fraction of a cost.

Single-cell RNA sequencing in Drosophila: Technologies and applications

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cell states and functions at the single-cell level. It has greatly revolutionized transcriptomic studies in many life science research fields, such as neurobiology, immunology, and developmental biology. With the fast development of both experimental platforms and bioinformatics approaches over the past decade, scRNA-seq is becoming economically feasible and experimentally practical for many biomedical laboratories. Drosophila has served as an excellent model organism for dissecting cellular and molecular mechanisms that underlie tissue development, adult cell function, disease, and aging. The recent application of scRNA-seq methods to Drosophila tissues has led to a number of exciting discoveries. In this review, I will provide a summary of recent scRNA-seq studies in Drosophila, focusing on technical approaches and biological applications. I will also discuss current challenges and future opportunities of making new discoveries using scRNA-seq in Drosophila. This article is categorized under:   Technologies > Analysis of the Transcriptome.

Molecular mechanisms underlying glyphosate resistance in bacteria

Glyphosate is a nonselective herbicide that kills weeds and other plants competing with crops. Glyphosate specifically inhibits the 5-enolpyruvyl-shikimate-3-phosphate (EPSP) synthase, thereby depleting the cell of EPSP serving as a precursor for biosynthesis of aromatic amino acids. Glyphosate is considered to be toxicologically safe for animals and humans. Therefore, it became the most-important herbicide in agriculture. However, its intensive application in agriculture is a serious environmental issue because it may negatively affect the biodiversity. A few years after the discovery of the mode of action of glyphosate, it has been observed that bacteria evolve glyphosate resistance by acquiring mutations in the EPSP synthase gene, rendering the encoded enzyme less sensitive to the herbicide. The identification of glyphosate-resistant EPSP synthase variants paved the way for engineering crops tolerating increased amounts of the herbicide. This review intends to summarize the molecular mechanisms underlying glyphosate resistance in bacteria. Bacteria can evolve glyphosate resistance by (i) reducing glyphosate sensitivity or elevating production of the EPSP synthase, by (ii) degrading or (iii) detoxifying glyphosate and by (iv) decreasing the uptake or increasing the export of the herbicide. The variety of glyphosate resistance mechanisms illustrates the adaptability of bacteria to anthropogenic substances due to genomic alterations.

The Burkholderia pseudomallei intracellular 'TRANSITome'

Prokaryotic cell transcriptomics has been limited to mixed or sub-population dynamics and individual cells within heterogeneous populations, which has hampered further understanding of spatiotemporal and stage-specific processes of prokaryotic cells within complex environments. Here we develop a 'TRANSITomic' approach to profile transcriptomes of single Burkholderia pseudomallei cells as they transit through host cell infection at defined stages, yielding pathophysiological insights. We find that B. pseudomallei transits through host cells during infection in three observable stages: vacuole entry; cytoplasmic escape and replication; and membrane protrusion, promoting cell-to-cell spread. The B. pseudomallei 'TRANSITome' reveals dynamic gene-expression flux during transit in host cells and identifies genes that are required for pathogenesis. We find several hypothetical proteins and assign them to virulence mechanisms, including attachment, cytoskeletal modulation, and autophagy evasion. The B. pseudomallei 'TRANSITome' provides prokaryotic single-cell transcriptomics information enabling high-resolution understanding of host-pathogen interactions.

Opening up the Single-Cell Toolbox for Microbial Natural Products Research

The diverse microbes that produce natural products represent an important source of novel therapeutics, drug leads, and scientific tools. However, the vast majority have not been grown in axenic culture and are members of complex communities. While meta-'omic methods such as metagenomics, -transcriptomics, and -proteomics reveal collective molecular features of this "microbial dark matter", the study of individual microbiome members can be challenging. To address these limits, a number of techniques with single-bacterial resolution have been developed in the last decade and a half. While several of these are embraced by microbial ecologists, there has been less use by researchers interested in mining microbes for natural products. In this review, we discuss the available and emerging techniques for targeted single-cell analysis with a particular focus on applications to the discovery and study of natural products.

Single-cell measurement of plasmid copy number and promoter activity

Accurate measurements of promoter activities are crucial for predictably building genetic systems. Here we report a method to simultaneously count plasmid DNA, RNA transcripts, and protein expression in single living bacteria. From these data, the activity of a promoter in units of RNAP/s can be inferred. This work facilitates the reporting of promoters in absolute units, the variability in their activity across a population, and their quantitative toll on cellular resources, all of which provide critical insights for cellular engineering.

Single-Cell Sequencing and Organoids: A Powerful Combination for Modelling Organ Development and Diseases

The development and function of a particular organ and the pathogenesis of various diseases remain intimately linked to the features of each cell type in the organ. Conventional messenger RNA- or protein-based methodologies often fail to elucidate the contribution of rare cell types, including some subpopulations of stem cells, short-lived progenitors and circulating tumour cells, thus hampering their applications in studies regarding organ development and diseases. The scRNA-seq technique represents a new approach for determining gene expression variability at the single-cell level. Organoids are new preclinical models that recapitulate complete or partial features of their original organ and are thought to be superior to cell models in mimicking the sophisticated spatiotemporal processes of the development and regeneration and diseases. In this review, we highlight recent advances in the field of scRNA-seq, organoids and their current applications and summarize the advantages of using a combination of scRNA-seq and organoid technology to model diseases and organ development.

Microbial single-cell RNA sequencing by split-pool barcoding

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

Multicellular and unicellular responses of microbial biofilms to stress

Biofilms are a ubiquitous mode of microbial life and display an increased tolerance to different stresses. Inside biofilms, cells may experience both externally applied stresses and internal stresses that emerge as a result of growth in spatially structured communities. In this review, we discuss the spatial scales of different stresses in the context of biofilms, and if cells in biofilms respond to these stresses as a collection of individual cells, or if there are multicellular properties associated with the response. Understanding the organizational level of stress responses in microbial communities can help to clarify multicellular functions of biofilms.

Efficient and cost-effective bacterial mRNA sequencing from low input samples through ribosomal RNA depletion

BACKGROUND

RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification.

RESULTS

EMBR-seq results in 90% of the sequenced RNA molecules from an E. coli culture deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq uses a single or a few oligonucleotides per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits for bacterial rRNA depletion, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA.

CONCLUSIONS

EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.

Microbial single-cell omics: the crux of the matter

Abstract

Single-cell genomics and transcriptomics can provide reliable context for assembled genome fragments and gene expression activity on the level of individual prokaryotic genomes. These methods are rapidly emerging as an essential complement to cultivation-based, metagenomics, metatranscriptomics, and microbial community-focused research approaches by allowing direct access to information from individual microorganisms, even from deep-branching phylogenetic groups that currently lack cultured representatives. Their integration and binning with environmental ‘omics data already provides unprecedented insights into microbial diversity and metabolic potential, enabling us to provide information on individual organisms and the structure and dynamics of natural microbial populations in complex environments. This review highlights the pitfalls and recent advances in the field of single-cell omics and its importance in microbiological and biotechnological studies.

Key points

• Single-cell omics expands the tree of life through the discovery of novel organisms, genes, and metabolic pathways.

• Disadvantages of metagenome-assembled genomes are overcome by single-cell omics.

• Functional analysis of single cells explores the heterogeneity of gene expression.

• Technical challenges still limit this field, thus prompting new method developments.

In vitro evolution of phi29 DNA polymerases through compartmentalized gene expression and rolling-circle replication

Phi29 DNA polymerase is widely used for DNA amplification through rolling-circle replication or multiple displacement amplification. Here, we performed completely in vitro artificial evolution of phi29 DNA polymerase by combining the in vitro compartmentalization and the gene expression-coupled rolling-circle replication of a circular DNA encoding the polymerase. We conducted the experiments in six different conditions composed of three different levels of inhibitor concentrations with two different DNA labeling methods. One of the experiments was performed in our previous study and the other five experiments were newly conducted in this study. Under all conditions, we found several mutations that enhance the rolling-circle amplification by the polymerase when it was expressed in the reconstituted gene expression system. Especially, a combinatorial mutant polymerase (K555T/D570N) exhibits significantly higher rolling-circle activity than the wild type. These highly active mutant polymerases would be useful for various applications.

Single-cell RNA-sequencing reports growth-condition-specific global transcriptomes of individual bacteria

Bacteria respond to changes in their environment with specific transcriptional programmes, but even within genetically identical populations these programmes are not homogenously expressed¹. Such transcriptional heterogeneity between individual bacteria allows genetically clonal communities to develop a complex array of phenotypes¹, examples of which include persisters that resist antibiotic treatment and metabolically specialized cells that emerge under nutrient-limiting conditions². Fluorescent reporter constructs have played a pivotal role in deciphering heterogeneous gene expression within bacterial populations³ but have been limited to recording the activity of single genes in a few genetically tractable model species, whereas the vast majority of bacteria remain difficult to engineer and/or even to cultivate. Single-cell transcriptomics is revolutionizing the analysis of phenotypic cell-to-cell variation in eukaryotes, but technical hurdles have prevented its robust application to prokaryotes. Here, using an improved poly(A)-independent single-cell RNA-sequencing protocol, we report the faithful capture of growth-dependent gene expression patterns in individual Salmonella and Pseudomonas bacteria across all RNA classes and genomic regions. These transcriptomes provide important reference points for single-cell RNA-sequencing of other bacterial species, mixed microbial communities and host-pathogen interactions.

A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast

Current methods for single-cell RNA sequencing (scRNA-seq) of yeast cells do not match the throughput and relative simplicity of the state-of-the-art techniques that are available for mammalian cells. In this study, we report how 10x Genomics' droplet-based single-cell RNA sequencing technology can be modified to allow analysis of yeast cells. The protocol, which is based on in-droplet spheroplasting of the cells, yields an order-of-magnitude higher throughput in comparison to existing methods. After extensive validation of the method, we demonstrate its use by studying the dynamics of the response of isogenic yeast populations to a shift in carbon source, revealing the heterogeneity and underlying molecular processes during this shift. The method we describe opens new avenues for studies focusing on yeast cells, as well as other cells with a degradable cell wall.

There is no hiding if you Seq: recent breakthroughs in Pseudomonas aeruginosa research revealed by genomic and transcriptomic next-generation sequencing

The advent of next-generation sequencing technology has revolutionized the field of prokaryotic genetics and genomics by allowing interrogation of entire genomes, transcriptomes and global transcription factor binding profiles. As more studies employing these techniques have been performed, the state of the art regarding prokaryotic gene regulation has developed from the level of individual genes to genetic regulatory networks and systems biology. When applied to bacterial pathogens, particularly valuable insights have been gained into the regulation of virulence-associated genes, their relative importance to bacterial survival in planktonic, biofilm or host infection scenarios, antimicrobial resistance and the molecular details of host-pathogen interactions. This review outlines some of the latest developments and applications of next-generation sequencing techniques that have used primarily Pseudomonas aeruginosa as a model system. We focus particularly on insights into Pseudomonas virulence and infection that have been gained from these approaches and the future directions in which this field could develop.

Single-Cell RNA Sequencing of Plant-Associated Bacterial Communities

Plants in soil are not solitary, hence continually interact with and obtain benefits from a community of microbes ("microbiome"). The meta-functional output from the microbiome results from complex interactions among the different community members with distinct taxonomic identities and metabolic capacities. Particularly, the bacterial communities of the root surface are spatially organized structures composed of root-attached biofilms and planktonic cells arranged in complex layers. With the distinct but coordinated roles among the different member cells, bacterial communities resemble properties of a multicellular organism. High throughput sequencing technologies have allowed rapid and large-scale analysis of taxonomic composition and metabolic capacities of bacterial communities. However, these methods are generally unable to reconstruct the assembly of these communities, or how the gene expression patterns in individual cells/species are coordinated within these communities. Single-cell transcriptomes of community members can identify how gene expression patterns vary among members of the community, including differences among different cells of the same species. This information can be used to classify cells based on functional gene expression patterns, and predict the spatial organization of the community. Here we discuss strategies for the isolation of single bacterial cells, mRNA enrichment, library construction, and analysis and interpretation of the resulting single-cell RNA-Seq datasets. Unraveling regulatory and metabolic processes at the single cell level is expected to yield an unprecedented discovery of mechanisms involved in bacterial recruitment, attachment, assembly, organization of the community, or in the specific interactions among the different members of these communities.

Microfluidic SlipChip device for multistep multiplexed biochemistry on a nanoliter scale

We have developed a multistep microfluidic device that expands the current SlipChip capabilities by enabling multiple steps of droplet merging and multiplexing. Harnessing the interfacial energy between carrier and sample phases, this manually operated device accurately meters nanoliter volumes of reagents and transfers them into on-device reaction wells. Judiciously shaped microfeatures and surface-energy traps merge droplets in a parallel fashion. Wells can be tuned for different volumetric capacities and reagent types, including for pre-spotted reagents that allow for unique identification of original well contents even after their contents are pooled. We demonstrate the functionality of the multistep SlipChip by performing RNA transcript barcoding on-device for synthetic spiked-in standards and for biologically derived samples. This technology is a good candidate for a wide range of biological applications that require multiplexing of multistep reactions in nanoliter volumes, including single-cell analyses.

Nature's recyclers: anaerobic microbial communities drive crude biomass deconstruction

Microbial communities within anaerobic ecosystems have evolved to degrade and recycle carbon throughout the earth. A number of strains have been isolated from anaerobic microbial communities, which are rich in carbohydrate active enzymes (CAZymes) to liberate fermentable sugars from crude plant biomass (lignocellulose). However, natural anaerobic communities host a wealth of microbial diversity that has yet to be harnessed for biotechnological applications to hydrolyze crude biomass into sugars and value-added products. This review highlights recent advances in 'omics' techniques to sequence anaerobic microbial genomes, decipher microbial membership, and characterize CAZyme diversity in anaerobic microbiomes. With a focus on the herbivore rumen, we further discuss methods to discover new CAZymes, including those found within multi-enzyme fungal cellulosomes. Emerging techniques to characterize the interwoven metabolism and spatial interactions between anaerobes are also reviewed, which will prove critical to developing a predictive understanding of anaerobic communities to guide in microbiome engineering.

Bacterial Single Cell Whole Transcriptome Amplification in Microfluidic Platform Shows Putative Gene Expression Heterogeneity

Single cell RNA sequencing is a technology that provides the capability of analyzing the transcriptome of a single cell from a population. So far, single cell RNA sequencing has been focused mostly on human cells due to the larger starting amount of RNA template for subsequent amplification. One of the major challenges of applying single cell RNA sequencing to microbial cells is to amplify the femtograms of the RNA template to obtain sufficient material for downstream sequencing with minimal contamination. To achieve this goal, efforts have been focused on multiround RNA amplification, but would introduce additional contamination and bias. In this work, we for the first time coupled a microfluidic platform with multiple displacement amplification technology to perform single cell whole transcriptome amplification and sequencing of Porphyromonas somerae, a microbe of interest in endometrial cancer, as a proof-of-concept demonstration of using single cell RNA sequencing tool to unveil gene expression heterogeneity in single microbial cells. Our results show that the bacterial single-cell gene expression regulation is distinct across different cells, supporting widespread heterogeneity.

Transcriptional analysis reveals the metabolic state of Burkholderia zhejiangensis CEIB S4-3 during methyl parathion degradation

Burkholderia zhejiangensis CEIB S4-3 has the ability to degrade methyl parathion (MP) and its main hydrolysis byproduct p-nitrophenol (PNP). According to genomic data, several genes related with metabolism of MP and PNP were identified in this strain. However, the metabolic state of the strain during the MP degradation has not been evaluated. In the present study, we analyzed gene expression changes during MP hydrolysis and PNP degradation through a transcriptomic approach. The transcriptional analysis revealed differential changes in the expression of genes involved in important cellular processes, such as energy production and conversion, transcription, amino acid transport and metabolism, translation, ribosomal structure and biogenesis, among others. Transcriptomic data also exhibited the overexpression of both PNP-catabolic gene clusters (pnpABA′E1E2FDC and pnpE1E2FDC) present in the strain. We found and validated by quantitative reverse transcription polymerase chain reaction the expression of the methyl parathion degrading gene, as well as the genes responsible for PNP degradation contained in two clusters. This proves the MP degradation pathway by the strain tested in this work. The exposure to PNP activates, in the first instance, the expression of the transcriptional regulators multiple antibiotic resistance regulator and Isocitrate Lyase Regulator (IclR), which are important in the regulation of genes from aromatic compound catabolism, as well as the expression of genes that encode transporters, permeases, efflux pumps, and porins related to the resistance to multidrugs and other xenobiotics. In the presence of the pesticide, 997 differentially expressed genes grouped in 104 metabolic pathways were observed. This report is the first to describe the transcriptomic analysis of a strain of B. zhejiangensis during the biodegradation of PNP.

Emergence of Bias During the Synthesis and Amplification of cDNA for scRNA-seq

The advent of single-cell omics technology has promoted our understanding of the genomic, epigenomic, and transcriptomic heterogeneity in individual cells. Compared to traditional sequencing studies using bulk cells, single-cell transcriptome technology is naturally more dynamic for in depth analysis of genomic variation resulting from cell division and is useful in unraveling the regulatory mechanisms of gene networks in many diseases. However, there are still some limitations of current single-cell RNA sequencing (scRNA-seq) protocols. Biases that arise during the RNA reverse transcription and cDNA pre-amplification steps are the most common problems and play pivotal roles in limiting the quantitative accuracy of scRNA-seq. In this review, we will describe how these biases emerge and impact scRNA-seq protocols. Moreover, we will introduce several current and convenient modified scRNA-seq methods that allow for bias to be decreased and estimated.

Technical Advances in Single-Cell RNA Sequencing and Applications in Normal and Malignant Hematopoiesis

Single-cell RNA sequencing (scRNA-seq) has been tremendously developed in the past decade owing to overcoming challenges associated with isolation of massive quantities of single cells. Previously, cell heterogeneity and low quantities of available biological material posed significant difficulties to scRNA-seq. Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of normal and malignant hematopoietic cells; this heterogeneity has often been ignored in omics studies. The application of scRNA-seq has profoundly changed our comprehension of many biological phenomena, including organ development and carcinogenesis. Hematopoiesis, is actually a maturation process for more than ten distinct blood and immune cells, and is thought to be critically involved in hematological homeostasis and in sustaining the physiological functions. However, aberrant hematopoiesis directly leads to hematological malignancy, and a deeper understanding of malignant hematopoiesis will provide deeper insights into diagnosis and prognosis for patients with hematological malignancies. Here, we aim to review the recent technical progress and future prospects for scRNA-seq, as applied in physiological and malignant hematopoiesis, in efforts to further understand the hematopoietic hierarchy and to illuminate personalized therapy and precision medicine approaches used in the clinical treatment of hematological malignancies.

Two Regulators, PA3898 and PA2100, Modulate the Pseudomonas aeruginosa Multidrug Resistance MexAB-OprM and EmrAB Efflux Pumps and Biofilm Formation

It is generally believed that the Pseudomonas aeruginosa biofilm matrix itself acts as a molecular sieve or sink that contributes to significant levels of drug resistance, but it is becoming more apparent that multidrug efflux pumps induced during biofilm growth significantly enhance resistance levels. We present here a novel transcriptional regulator, PA3898, which controls biofilm formation and multidrug efflux pumps in P. aeruginosa A mutant of this regulator significantly reduced the ability of P. aeruginosa to produce biofilm in vitro and affected its in vivo fitness and pathogenesis in Drosophila melanogaster and BALB/c mouse lung infection models. Transcriptome analysis revealed that PA3898 modulates essential virulence genes/pathways, including multidrug efflux pumps and phenazine biosynthesis. Chromatin immunoprecipitation sequencing (ChIP-seq) identified its DNA binding sequences and confirmed that PA3898 directly interacts with promoter regions of four genes/operons, two of which are mexAB-oprM and phz2 Coimmunoprecipitation revealed a regulatory partner of PA3898 as PA2100, and both are required for binding to DNA in electrophoretic mobility shift assays. PA3898 and PA2100 were given the names MdrR1 and MdrR2, respectively, as novel repressors of the mexAB-oprM multidrug efflux operon and activators for another multidrug efflux pump, EmrAB. The interaction between MdrR1 and MdrR2 at the promoter regions of their regulons was further characterized via localized surface plasmon resonance and DNA footprinting. These regulators directly repress the mexAB-oprM operon, independent of its well-established MexR regulator. Mutants of mdrR1 and mdrR2 caused increased resistance to multiple antibiotics in P. aeruginosa, validating the significance of these newly discovered regulators.

Cytometry meets next-generation sequencing - RNA-Seq of sorted subpopulations reveals regional replication and iron-triggered prophage induction in Corynebacterium glutamicum

Phenotypic diversification is key to microbial adaptation. Currently, advanced technological approaches offer insights into cell-to-cell variation of bacterial populations at a spatiotemporal resolution. However, the underlying molecular causes or consequences often remain obscure. In this study, we developed a workflow combining fluorescence-activated cell sorting and RNA-sequencing, thereby allowing transcriptomic analysis of 106 bacterial cells. As a proof of concept, the workflow was applied to study prophage induction in a subpopulation of Corynebacterium glutamicum. Remarkably, both the phage genes and flanking genomic regions of the CGP3 prophage revealed significantly increased coverage upon prophage induction - a phenomenon that to date has been obscured by bulk approaches. Genome sequencing of prophage-induced populations suggested regional replication at the CGP3 locus in C. glutamicum. Finally, the workflow was applied to unravel iron-triggered prophage induction in early exponential cultures. Here, an up-shift in iron levels resulted in a heterogeneous response of an SOS (PdivS) reporter. RNA-sequencing of the induced subpopulation confirmed induction of the SOS response triggering also activation of the CGP3 prophage. The fraction of CGP3-induced cells was enhanced in a mutant lacking the iron regulator DtxR suffering from enhanced iron uptake. Altogether, these findings demonstrate the potential of the established workflow to gain insights into the phenotypic dynamics of bacterial populations.

Comprehensive off-target analysis of dCas9-SAM-mediated HIV reactivation via long noncoding RNA and mRNA profiling

Background

CRISPR/CAS9 (epi)genome editing revolutionized the field of gene and cell therapy. Our previous study demonstrated that a rapid and robust reactivation of the HIV latent reservoir by a catalytically-deficient Cas9 (dCas9)-synergistic activation mediator (SAM) via HIV long terminal repeat (LTR)-specific MS2-mediated single guide RNAs (msgRNAs) directly induces cellular suicide without additional immunotherapy. However, potential off-target effect remains a concern for any clinical application of Cas9 genome editing and dCas9 epigenome editing. After dCas9 treatment, potential off-target responses have been analyzed through different strategies such as mRNA sequence analysis, and functional screening. In this study, a comprehensive analysis of the host transcriptome including mRNA, lncRNA, and alternative splicing was performed using human cell lines expressing dCas9-SAM and HIV-targeting msgRNAs.

Results

The control scrambled msgRNA (LTR_Zero), and two LTR-specific msgRNAs (LTR_L and LTR_O) groups show very similar expression profiles of the whole transcriptome. Among 839 identified lncRNAs, none exhibited significantly different expression in LTR_L vs. LTR_Zero group. In LTR_O group, only TERC and scaRNA2 lncRNAs were significantly decreased. Among 142,791 mRNAs, four genes were differentially expressed in LTR_L vs. LTR_Zero group. There were 21 genes significantly downregulated in LTR_O vs. either LTR_Zero or LTR_L group and one third of them are histone related. The distributions of different types of alternative splicing were very similar either within or between groups. There were no apparent changes in all the lncRNA and mRNA transcripts between the LTR_L and LTR_Zero groups.

Conclusion

This is an extremely comprehensive study demonstrating the rare off-target effects of the HIV-specific dCas9-SAM system in human cells. This finding is encouraging for the safe application of dCas9-SAM technology to induce target-specific reactivation of latent HIV for an effective “shock-and-kill” strategy.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0394-2) contains supplementary material, which is available to authorized users.

Emergent Properties of Microbial Activity in Heterogeneous Soil Microenvironments: Different Research Approaches Are Slowly Converging, Yet Major Challenges Remain

Over the last 60 years, soil microbiologists have accumulated a wealth of experimental data showing that the bulk, macroscopic parameters (e.g., granulometry, pH, soil organic matter, and biomass contents) commonly used to characterize soils provide insufficient information to describe quantitatively the activity of soil microorganisms and some of its outcomes, like the emission of greenhouse gasses. Clearly, new, more appropriate macroscopic parameters are needed, which reflect better the spatial heterogeneity of soils at the microscale (i.e., the pore scale) that is commensurate with the habitat of many microorganisms. For a long time, spectroscopic and microscopic tools were lacking to quantify processes at that scale, but major technological advances over the last 15 years have made suitable equipment available to researchers. In this context, the objective of the present article is to review progress achieved to date in the significant research program that has ensued. This program can be rationalized as a sequence of steps, namely the quantification and modeling of the physical-, (bio)chemical-, and microbiological properties of soils, the integration of these different perspectives into a unified theory, its upscaling to the macroscopic scale, and, eventually, the development of new approaches to measure macroscopic soil characteristics. At this stage, significant progress has been achieved on the physical front, and to a lesser extent on the (bio)chemical one as well, both in terms of experiments and modeling. With regard to the microbial aspects, although a lot of work has been devoted to the modeling of bacterial and fungal activity in soils at the pore scale, the appropriateness of model assumptions cannot be readily assessed because of the scarcity of relevant experimental data. For significant progress to be made, it is crucial to make sure that research on the microbial components of soil systems does not keep lagging behind the work on the physical and (bio)chemical characteristics. Concerning the subsequent steps in the program, very little integration of the various disciplinary perspectives has occurred so far, and, as a result, researchers have not yet been able to tackle the scaling up to the macroscopic level. Many challenges, some of them daunting, remain on the path ahead. Fortunately, a number of these challenges may be resolved by brand new measuring equipment that will become commercially available in the very near future.

Novel dual regulators of Pseudomonas aeruginosa essential for productive biofilms and virulence

Gene regulation network in Pseudomonas aeruginosa is complex. With a relatively large genome (6.2 Mb), there is a significant portion of genes that are proven or predicted to be transcriptional regulators. Many of these regulators have been shown to play important roles in biofilm formation and maintenance. In this study, we present a novel transcriptional regulator, PA1226, which modulates biofilm formation and virulence in P. aeruginosa. Mutation in the gene encoding this regulator abolished the ability of P. aeruginosa to produce biofilms in vitro, without any effect on the planktonic growth. This regulator is also essential for the in vivo fitness and pathogenesis in both Drosophila melanogaster and BALB/c mouse lung infection models. Transcriptome analysis revealed that PA1226 regulates many essential virulence genes/pathways, including those involved in alginate, pili, and LPS biosynthesis. Genes/operons directly regulated by PA1226 and potential binding sequences were identified via ChIP-seq. Attempts to confirm the binding sequences by electrophoretic mobility shift assay led to the discovery of a co-regulator, PA1413, via co-immunoprecipitation assay. PA1226 and PA1413 were shown to bind collaboratively to the promoter regions of their regulons. A model is proposed, summarizing our finding on this novel dual-regulation system.

Global and targeted approaches to single-cell transcriptome characterization

Analysing transcriptomes of cell populations is a standard molecular biology approach to understand how cells function. Recent methodological development has allowed performing similar experiments on single cells. This has opened up the possibility to examine samples with limited cell number, such as cells of the early embryo, and to obtain an understanding of heterogeneity within populations such as blood cell types or neurons. There are two major approaches for single-cell transcriptome analysis: quantitative reverse transcription PCR (RT-qPCR) on a limited number of genes of interest, or more global approaches targeting entire transcriptomes using RNA sequencing. RT-qPCR is sensitive, fast and arguably more straightforward, while whole-transcriptome approaches offer an unbiased perspective on a cell's expression status.

Recent Developments in Single-Cell RNA-Seq of Microorganisms

Single-cell transcriptome analysis through next-generation sequencing (single-cell RNA-seq) has been used broadly to address important biological questions. It has proved to be very powerful, and many exciting new biological discoveries have been achieved in the last decade. Its application has greatly improved our understanding of diverse biological processes and the underlying molecular mechanisms, an understanding that would not have been achievable by conventional analysis based on bulk populations. However, so far, single-cell RNA-seq analysis has been used mostly for higher organisms. For microorganisms, single-cell RNA-seq has not been widely used, mainly because the stiff cell wall prevents effective lysis, much less starting RNA material is obtained, and the RNA lacks polyadenylated tails for universal priming of mRNA molecules. In general, the detection efficiency of current single-cell RNA-seq technologies is very low, and further development or improvement of these technologies is required for exploring the microbial world at single-cell resolution. Here, we briefly review recent developments in single-cell RNA-seq of microorganisms and discuss current challenges and future directions.

Spatial transcriptomes within the Pseudomonas aeruginosa biofilm architecture

Bacterial cooperative associations and dynamics in biofilm microenvironments are of special interest in recent years. Knowledge of localized gene‐expression and corresponding bacterial behaviors within the biofilm architecture at a global scale has been limited, due to a lack of robust technology to study limited number of cells in stratified layers of biofilms. With our recent pioneering developments in single bacterial cell transcriptomic analysis technology, we generated herein an unprecedented spatial transcriptome map of the mature in vitro Pseudomonas aeruginosa biofilm model, revealing contemporaneous yet altered bacterial behaviors at different layers within the biofilm architecture (i.e., surface, middle and interior of the biofilm). Many genes encoding unknown functions were highly expressed at the biofilm‐solid interphase, exposing a critical gap in the knowledge of their activities that may be unique to this interior niche. Several genes of unknown functions are critical for biofilm formation. The in vivo importance of these unknown proteins was validated in invertebrate (fruit fly) and vertebrate (mouse) models. We envisage the future value of this report to the community, in aiding the further pathophysiological understanding of P. aeruginosa biofilms. Our approach will open doors to the study of bacterial functional genomics of different species in numerous settings.

Beyond the bulk: disclosing the life of single microbial cells

Microbial single cell analysis has led to discoveries that are beyond what can be resolved with population-based studies. It provides a pristine view of the mechanisms that organize cellular physiology, unbiased by population heterogeneity or uncontrollable environmental impacts. A holistic description of cellular functions at the single cell level requires analytical concepts beyond the miniaturization of existing technologies, defined but uncontrolled by the biological system itself. This review provides an overview of the latest advances in single cell technologies and demonstrates their potential. Opportunities and limitations of single cell microbiology are discussed using selected application-related examples.