scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing

Droplet microfluidics: unveiling the hidden complexity of the human microbiome

The human body harbors diverse microbial communities essential for maintaining health and influencing disease processes. Droplet microfluidics, a precise and high-throughput platform for manipulating microscale droplets, has become vital in advancing microbiome research. This review introduces the foundational principles of droplet microfluidics, its operational capabilities, and wide-ranging applications. We emphasize its role in enhancing single-cell sequencing technologies, particularly genome and RNA sequencing, transforming our understanding of microbial diversity, gene expression, and community dynamics. We explore its critical function in isolating and cultivating traditionally unculturable microbes and investigating microbial activity and interactions, facilitating deeper insight into community behavior and metabolic functions. Lastly, we highlight its broader applications in microbial analysis and its potential to revolutionize human health research by driving innovations in diagnostics, therapeutic development, and personalized medicine. This review provides a comprehensive overview of droplet microfluidics' impact on microbiome research, underscoring its potential to transform our understanding of microbial dynamics and their relevance to health and disease.

Dissecting host-microbe interactions with modern functional genomics

Interrogation of host-microbe interactions has long been a source of both basic discoveries and benefits to human health. Here, we review the role that functional genomics approaches have played in such efforts, with an emphasis on recent examples that have harnessed technological advances to provide mechanistic insight at increased scale and resolution. Finally, we discuss how concurrent innovations in model systems and genetic tools have afforded opportunities to interrogate additional types of host-microbe relationships, such as those in the mammalian gut. Bringing these innovations together promises many exciting discoveries ahead.

Multi-omics analyses of cancer-linked clinical salmonellae reveal bacterial-induced host metabolic shift and mTOR-dependent cell transformation

Salmonellae are associated epidemiologically and experimentally with colon cancer. To understand how Salmonella induces cell transformation, we performed multi-omics and phenotypic analyses of Salmonella clinical strains isolated from patients later diagnosed with colon cancer (case strains) and control strains from patients without cancer. We show that high transformation efficiency is a frequent intrinsic feature of clinical (case and control) salmonellae, yet case strains showed higher transformation efficiency than control strains. Transformation efficiency correlates with gene expression, nutrient utilization, and intracellular virulence, but not with genetic features, suggesting a phenotypic convergence of Salmonella strains resulting in cell transformation. We show that both bacterial entry and intracellular replication are required for host cell transformation and are associated with hyperactivation of the mTOR pathway. Strikingly, transiently inactivating mTOR through chemical inhibition reverses the transformation phenotype instigated by Salmonella infection. This suggests that targeting the mTOR pathway could prevent the development of Salmonella-induced tumors.

Genetic Approaches for Identifying and Characterizing Effectors in Bacterial Pathogens

Microbial pathogens have coevolved with their hosts, often for millions of years, and in the process have developed a variety of virulence mechanisms to ensure their survival, typically at the host's expense. At the center of this host-pathogen warfare are proteins called effectors that are delivered by bacteria into their host where they alter the intracellular environment to promote bacterial proliferation. Many effectors are believed to have been acquired by the bacteria from their host during evolution, explaining why researchers are keen to understand their function, as this information may provide insight into both microbial virulence strategies and biological processes that happen within our own cells. Help for accomplishing this goal has come from the recent development of increasingly powerful genetic approaches, which are the focus of this review.

Comparison of global transcriptomes for nontyphoidal Salmonella clinical isolates from pediatric patients with and without bacteremia after their interaction with human intestinal epithelial cells in vitro

BACKGROUND

Nontyphoidal Salmonella (NTS) outbreaks of invasive diseases are increasing. Whether the genetic diversity of invasive NTS correlates with the clinical characteristics and bacteremia development in NTS infections remains unclear. In this study, we compared the global transcriptomes between bacteremic and nonbacteremic NTS strains after their interaction with human intestinal epithelial cells in vitro.

METHODS

We selected clinical isolates obtained from stool and blood samples of patients with or without bacteremia and patients with high and low C-reactive protein (CRP) levels. The bacterial RNA samples were isolated after coculturing with Caco-2 cells for RNA sequencing and subsequent analyses.

RESULTS

CRP is an unreliable predictive maker for NTS bacteremia with a median CRP level of 1.6 mg/dL. Certain Salmonella Pathogenicity Island (SPI)-1 genes (sipC, sipA, sicA, sipD, and sipB), SPI-2 genes (ssaP, ssrA, and ssaS), and six SPI-4 genes (siiA, siiB, siiC, siiD, siiE, and siiF) remained upregulated in the bacteremic blood-derived strains but significantly downregulated in the nonbacteremic strains after their interaction with Caco-2 cells. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis identified that arginine biosynthesis, ascorbate and aldarate metabolism, and phosphotransferase system pathways were activated in bacteremic NTS strains after Caco-2 cell priming.

CONCLUSION

CRP levels were not correlated with bacteremia development. Significant regulation of certain SPI genes in bacteremic NTS strains after Caco-2 cell priming; bacteremia development might be influenced by the host immune response and the extent to which specific metabolism pathways in NTS strains can be prevented from invading the bloodstream.

Unraveling the intricacies of host-pathogen interaction through single-cell genomics

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions.

Advances in single-cell sequencing technology in microbiome research

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

Emerging tools for uncovering genetic and transcriptomic heterogeneities in bacteria

Bacterial communities display an astonishing degree of heterogeneities among their constituent cells across both the genomic and transcriptomic levels, giving rise to diverse social interactions and stress-adaptation strategies indispensable for proliferating in the natural environment (Ackermann in Nat Rev Microbiol 13:497-508, 2015). Our knowledge about bacterial heterogeneities and their physiological ramifications critically depends on our ability to unambiguously resolve the genetic and phenotypic states of the individual cells that make up the population. In this short review, I highlight several recently developed methods for studying bacterial heterogeneities, primarily focusing on single-cell techniques based on advanced sequencing and microscopy technologies. I will discuss the working principle of each technique as well as the types of problems each technique is best positioned to address. With significant improvements in resolution and throughput, these emerging tools together offer unprecedented and complementary views of various types of heterogeneities found within bacterial populations, paving the way for mechanistic dissections and systematic interventions in laboratory and clinical settings.

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.

High-throughput identification of Toxoplasma gondii effector proteins that target host cell transcription

Intracellular pathogens and other endosymbionts reprogram host cell transcription to suppress immune responses and recalibrate biosynthetic pathways. This reprogramming is critical in determining the outcome of infection or colonization. We combine pooled CRISPR knockout screening with dual host-microbe single-cell RNA sequencing, a method we term dual perturb-seq, to identify the molecular mediators of these transcriptional interactions. Applying dual perturb-seq to the intracellular pathogen Toxoplasma gondii, we are able to identify previously uncharacterized effector proteins and directly infer their function from the transcriptomic data. We show that TgGRA59 contributes to the export of other effector proteins from the parasite into the host cell and identify an effector, TgSOS1, that is necessary for sustained host STAT6 signaling and thereby contributes to parasite immune evasion and persistence. Together, this work demonstrates a tool that can be broadly adapted to interrogate host-microbe transcriptional interactions and reveal mechanisms of infection and immune evasion.

Microbiome characteristics description of COVID-19 patients based on bulk RNA-seq and scRNA-Seq data

After infection with SARS-CoV-2, the microbiome inside the human body changes dramatically. By re-annotating microbial sequences in bulk RNA-seq and scRNA-seq data of COVID-19 patients, we described the cellular microbial landscape of COVID-19 patients and identified characteristic microorganisms in various tissues. We found that Acinetobacter lwoffii was highly correlated with COVID-19 symptoms and might disrupt some pathways of patients by interacting with the host and other microbes, such as Klebsiella pneumoniae. We further identified characteristic microorganisms specific to cell type, indicating the enrichment preference of some microbes. We also revealed the co-infection of SARS-CoV-2 with hMPV, which may cause the development of COVID-19. Overall, we demonstrated that the presence of intracellular microorganisms in COVID-19 patients and the synergies between microorganisms were strongly correlated with disease progression, providing a theoretical basis for COVID-19 treatment in a certain extent.

scDual-Seq of Toxoplasma gondii-infected mouse BMDCs reveals heterogeneity and differential infection dynamics

Dendritic cells and macrophages are integral parts of the innate immune system and gatekeepers against infection. The protozoan pathogen, Toxoplasma gondii, is known to hijack host immune cells and modulate their immune response, making it a compelling model to study host-pathogen interactions. Here we utilize single cell Dual RNA-seq to parse out heterogeneous transcription of mouse bone marrow-derived dendritic cells (BMDCs) infected with two distinct genotypes of T. gondii parasites, over multiple time points post infection. We show that the BMDCs elicit differential responses towards T. gondii infection and that the two parasite lineages distinctly manipulate subpopulations of infected BMDCs. Co-expression networks define host and parasite genes, with implications for modulation of host immunity. Integrative analysis validates previously established immune pathways and additionally, suggests novel candidate genes involved in host-pathogen interactions. Altogether, this study provides a comprehensive resource for characterizing host-pathogen interplay at high-resolution.

Paired single-cell host profiling with multiplex-tagged bacterial mutants reveals intracellular virulence-immune networks

Encounters between host cells and intracellular bacterial pathogens lead to complex phenotypes that determine the outcome of infection. Single-cell RNA sequencing (scRNA-seq) is increasingly used to study the host factors underlying diverse cellular phenotypes but has limited capacity to analyze the role of bacterial factors. Here, we developed scPAIR-seq, a single-cell approach to analyze infection with a pooled library of multiplex-tagged, barcoded bacterial mutants. Infected host cells and barcodes of intracellular bacterial mutants are both captured by scRNA-seq to functionally analyze mutant-dependent changes in host transcriptomes. We applied scPAIR-seq to macrophages infected with a library of Salmonella Typhimurium secretion system effector mutants. We analyzed redundancy between effectors and mutant-specific unique fingerprints and mapped the global virulence network of each individual effector by its impact on host immune pathways. ScPAIR-seq is a powerful tool to untangle bacterial virulence strategies and their complex interplay with host defense strategies that drive infection outcome.

Could the tumor-associated microbiota be the new multi-faceted player in the tumor microenvironment?

Microorganisms have been identified in tumor specimens for over a century. It is only in recent years that tumor-associated microbiota has become a rapidly expanding field. Assessment techniques encompass methods at the frontiers of molecular biology, microbiology, and histology, requiring a transdisciplinary process to carefully decipher this new component of the tumor microenvironment. Due to the low biomass, the study of tumor-associated microbiota poses technical, analytical, biological, and clinical challenges and must be approached as a whole. To date, several studies have begun to shed light on the composition, functions, and clinical relevance of the tumor-associated microbiota. This new piece of the tumor microenvironment puzzle could potentially change the way we think about and treat patients with cancer.

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.

High-throughput microfluidic droplets in biomolecular analytical system: A review

Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.

Improved Bacterial Single-Cell RNA-Seq through Automated MATQ-Seq and Cas9-Based Removal of rRNA Reads

Bulk RNA sequencing technologies have provided invaluable insights into host and bacterial gene expression and associated regulatory networks. Nevertheless, the majority of these approaches report average expression across cell populations, hiding the true underlying expression patterns that are often heterogeneous in nature. Due to technical advances, single-cell transcriptomics in bacteria has recently become reality, allowing exploration of these heterogeneous populations, which are often the result of environmental changes and stressors. In this work, we have improved our previously published bacterial single-cell RNA sequencing (scRNA-seq) protocol that is based on multiple annealing and deoxycytidine (dC) tailing-based quantitative scRNA-seq (MATQ-seq), achieving a higher throughput through the integration of automation. We also selected a more efficient reverse transcriptase, which led to reduced cell loss and higher workflow robustness. Moreover, we successfully implemented a Cas9-based rRNA depletion protocol into the MATQ-seq workflow. Applying our improved protocol on a large set of single Salmonella cells sampled over different growth conditions revealed improved gene coverage and a higher gene detection limit compared to our original protocol and allowed us to detect the expression of small regulatory RNAs, such as GcvB or CsrB at a single-cell level. In addition, we confirmed previously described phenotypic heterogeneity in Salmonella in regard to expression of pathogenicity-associated genes. Overall, the low percentage of cell loss and high gene detection limit makes the improved MATQ-seq protocol particularly well suited for studies with limited input material, such as analysis of small bacterial populations in host niches or intracellular bacteria. IMPORTANCE Gene expression heterogeneity among isogenic bacteria is linked to clinically relevant scenarios, like biofilm formation and antibiotic tolerance. The recent development of bacterial single-cell RNA sequencing (scRNA-seq) enables the study of cell-to-cell variability in bacterial populations and the mechanisms underlying these phenomena. Here, we report a scRNA-seq workflow based on MATQ-seq with increased robustness, reduced cell loss, and improved transcript capture rate and gene coverage. Use of a more efficient reverse transcriptase and the integration of an rRNA depletion step, which can be adapted to other bacterial single-cell workflows, was instrumental for these improvements. Applying the protocol to the foodborne pathogen Salmonella, we confirmed transcriptional heterogeneity across and within different growth phases and demonstrated that our workflow captures small regulatory RNAs at a single-cell level. Due to low cell loss and high transcript capture rates, this protocol is uniquely suited for experimental settings in which the starting material is limited, such as infected tissues.

Untangling Cellular Host-Pathogen Encounters at Infection Bottlenecks

Bacterial pathogens can invade the tissue and establish a protected intracellular niche at the site of invasion that can spread locally (e.g., microcolonies) or to systemic sites (e.g., granulomas). Invasion of the tissue and establishment of intracellular infection are rare events that are difficult to study in the in vivo setting but have critical clinical consequences, such as long-term carriage, reinfections, and emergence of antibiotic resistance. Here, I discuss Salmonella interactions with its host macrophage during early stages of infection and their critical role in determining infection outcome. The dynamics of host-pathogen interactions entail highly heterogenous host immunity, bacterial virulence, and metabolic cross talk, requiring in vivo analysis at single-cell resolution. I discuss models and single-cell approaches that provide a global understanding of the establishment of a protected intracellular niche within the tissue and the host-pathogen landscape at infection bottlenecks during early stages of infection. Studying cellular host-pathogen interactions in vivo can improve our knowledge of the trajectory of infection between the initial inoculation with a dose of pathogens and the appearance of symptoms of disease.

Proteomics Profiling Reveals Regulation of Immune Response to Salmonella enterica Serovar Typhimurium Infection in Mice

Regulation of the immune response to Salmonella enterica serovar Typhimurium (S. Typhimurium) infection is a complex process, influenced by the interaction between genetic and environmental factors. Different inbred strains of mice exhibit distinct levels of resistance to S. Typhimurium infection, ranging from susceptible (e.g., C57BL/6J) to resistant (e.g., DBA/2J) strains. However, the underlying molecular mechanisms contributing to the host response remain elusive. In this study, we present a comprehensive proteomics profiling of spleen tissue from C57BL/6J and DBA/2J strains with different doses of S. Typhimurium infection by tandem mass tag labeling coupled with two-dimensional liquid chromatography-tandem mass spectrometry (TMT-LC/LC-MS/MS). We identified and quantified 3,986 proteins, resulting in 475 differentially expressed proteins (DEPs) between C57BL/6J and DBA/2J strains. Functional enrichment analysis unveiled that the mechanisms of innate immune responses to S. Typhimurium infection could be associated with several signaling pathways, including the interferon (IFN) signaling pathway. We experimentally validated the roles of the IFN signaling pathway in the innate immune response to S. Typhimurium infection using an IFN-γ neutralization assay. We further illustrated the importance of macrophage and proinflammatory cytokines in the mechanisms underlying the resistance to S. Typhimurium using quantitative reverse transcription-PCR (qRT-PCR). Taken together, our results provided new insights into the genetic regulation of the immune response to S. Typhimurium infection in mice and might lead to the discovery of potential protein targets for controlling salmonellosis.

A MATQ-seq-Based Protocol for Single-Cell RNA-seq in Bacteria

Microbes exhibit an extraordinary capacity to adapt their physiology to different environments using phenotypic heterogeneity. However, the majority of gene regulation studies are conducted in bulk reflecting only averaged gene expression levels across millions of cells. Bacterial single-cell RNA-seq (scRNA-seq) can overcome this by enabling whole transcriptome and unbiased analysis of microbes at the single-cell level. Here, we describe a detailed workflow of single-cell RNA-seq based on the multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq) protocol. Following adjustments to the original eukaryotic protocol, the workflow was applied to two major human pathogens Salmonella enterica serovar Typhimurium (henceforth Salmonella) and Pseudomonas aeruginosa (henceforth Pseudomonas). The development of bacterial scRNA-seq protocols offers promising avenues to explore the molecular programs underlying phenotypic heterogeneity on the transcriptome level in different settings such as infection, persistence, ecology, and biofilms.

Genome-Wide Analysis of Gene Expression Noise Brought About by Transcriptional Regulation in Pseudomonas aeruginosa

The part of expression noise that is brought about by transcriptional regulation (represented here as NTR) is an important criterion for estimating the regulatory mode of a gene. However, characterization of NTR is an under-explored area, and there is little knowledge regarding the genome-wide NTR in the model pathogen Pseudomonas aeruginosa. Here, with a library of dual-color transcriptional reporters, we estimated the NTR for over 90% of the promoters in P. aeruginosa. Most promoters exhibit low NTR, while 42 and 115 promoters with high NTR were screened out in the exponential and the stationary growth phases, respectively. Specifically, a rearrangement of NTR was found in promoters involved in amino acid metabolism when bacteria enter the exponential phase. In addition, during the stationary phase, high NTR was found in a wide range of iron-related promoters involving siderophore synthesis and heme uptake, ExsA-regulated promoters involving bacterial virulence, and FleQ-regulated promoters involving biofilm development. We also found a large-scale negative dependence of transcriptional regulation between high-NTR promoters belonging to different functional categories. Our findings offer a global view of transcriptional heterogeneity in P. aeruginosa. IMPORTANCE The phenotypic diversity of Pseudomonas aeruginosa is frequently observed in research, suggesting that bacteria adopt strategies such as bet-hedging to survive ever-changing environments. Gene expression noise (GEN) is the major source of phenotypic diversity. Large GEN from transcriptional regulation (represented as NTR) represent an evolutionary necessity to maintain the copy number diversity of certain proteins in the population. Here, we provide a system-wide view of NTR in P. aeruginosa under nutrient-rich and stressed conditions. High NTR was found in genes involved in flagella biosynthesis and amino acid metabolism under both conditions. Specially, iron acquisition genes exhibited high NTR in the stressed condition, suggesting a great diversity of iron physiology in P. aeruginosa. We further revealed a global negative dependence of transcriptional regulation between those high-NTR genes under the stressed condition, suggesting a mutually exclusive relationship between different bacterial survival strategies.

Developing New Tools to Fight Human Pathogens: A Journey through the Advances in RNA Technologies

A long scientific journey has led to prominent technological advances in the RNA field, and several new types of molecules have been discovered, from non-coding RNAs (ncRNAs) to riboswitches, small interfering RNAs (siRNAs) and CRISPR systems. Such findings, together with the recognition of the advantages of RNA in terms of its functional performance, have attracted the attention of synthetic biologists to create potent RNA-based tools for biotechnological and medical applications. In this review, we have gathered the knowledge on the connection between RNA metabolism and pathogenesis in Gram-positive and Gram-negative bacteria. We further discuss how RNA techniques have contributed to the building of this knowledge and the development of new tools in synthetic biology for the diagnosis and treatment of diseases caused by pathogenic microorganisms. Infectious diseases are still a world-leading cause of death and morbidity, and RNA-based therapeutics have arisen as an alternative way to achieve success. There are still obstacles to overcome in its application, but much progress has been made in a fast and effective manner, paving the way for the solid establishment of RNA-based therapies in the future.

Compartmentalization of the host microbiome: how tumor microbiota shapes checkpoint immunotherapy outcome and offers therapeutic prospects

The host microbiome is polymorphic, compartmentalized, and composed of distinctive tissue microbiomes. While research in the field of cancer immunotherapy has provided an improved understanding of the interaction with the gastrointestinal microbiome, the significance of the tumor-associated microbiome has only recently been grasped. This article provides a state-of-the-art review about the tumor-associated microbiome and sheds light on how local tumor microbiota shapes anticancer immunity and influences checkpoint immunotherapy outcome. The direct route of interaction between cancer cells, immune cells, and microbiota in the tumor microenvironment is emphasized and advocates a focus on the tumor-associated microbiome in addition to the spatially separated gut compartment. Since the mechanisms underlying checkpoint immunotherapy modulation by tumor-associated microbiota remain largely elusive, future research should dissect the pathways involved and outline strategies to therapeutically modulate microbes and their products within the tumor microenvironment. A more detailed knowledge about the mechanisms governing the composition and functional quality of the tumor microbiome will improve cancer immunotherapy and advance precision medicine for solid tumors.

The tempo and mode of gene regulatory programs during bacterial infection

Innate immune recognition of bacterial pathogens is a key determinant of the ensuing systemic response, and host or pathogen heterogeneity in this early interaction can impact the course of infection. To gain insight into host response heterogeneity, we investigate macrophage inflammatory dynamics using primary human macrophages infected with Group B Streptococcus. Transcriptomic analysis reveals discrete cellular states within responding macrophages, one of which consists of four sub-states, reflecting inflammatory activation. Infection with six additional bacterial species-Staphylococcus aureus, Listeria monocytogenes, Enterococcus faecalis, Yersinia pseudotuberculosis, Shigella flexneri, and Salmonella enterica-recapitulates these states, though at different frequencies. We show that modulating the duration of infection and the presence of a toxin impacts inflammatory trajectory dynamics. We provide evidence for this trajectory in infected macrophages in an in vivo model of Staphylococcus aureus infection. Our cell-state analysis defines a framework for understanding inflammatory activation dynamics in response to bacterial infection.

Reimagining the future of African brain health: Perspectives for basic research on the pathogenesis of cryptococcal meningitis

Cryptococcal meningitis is a fatal opportunistic infection of the brain and a leading cause of neurological damage and death in immunocompromised individuals. This neglected fungal disease of the brain is a huge burden on the health systems of developing countries, especially in Sub-Saharan Africa, where up to 25% of people living with HIV/AIDS succumb to it. Cryptococcal fungal cells have a predilection for the brain and they are capable of traversing the blood brain barrier and invade the brain where they cause infection, inflammation and a disruption of normal brain function. A robust host neuroimmune response is critical for pathogen clearance and survival, and a good understanding of the mechanisms underlying its development in the host is critical for the development of effective treatments. However, past basic research studies have been focussed on the characteristics of the fungus and its effect on the peripheral immune system; with little attention paid to how it interacts with brain immune cells. This mini review briefly discusses the paucity of basic research data on the neuroimmune response to cryptococcal infection, raises pertinent questions on how the brain cells respond to the fungal infection, and thereafter discusses models, techniques and advanced technologies that could be useful for carrying out high-throughput research on the pathogenesis of cryptococcal meningitis.

Single-Cell Genomics: Enabling the Functional Elucidation of Infectious Diseases in Multi-Cell Genomes

Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host-pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.

Understanding the pathogenesis of infectious diseases by single-cell RNA sequencing

Infections are highly orchestrated and dynamic processes, which involve both pathogen and host. Transcriptional profiling at the single-cell level enables the analysis of cell diversity, heterogeneity of the immune response, and detailed molecular mechanisms underlying infectious diseases caused by bacteria, viruses, fungi, and parasites. Herein, we highlight recent remarkable advances in single-cell RNA sequencing (scRNA-seq) technologies and their applications in the investigation of host-pathogen interactions, current challenges and potential prospects for disease treatment are discussed as well. We propose that with the aid of scRNA-seq, the mechanism of infectious diseases will be further revealed thus inspiring the development of novel interventions and therapies.

Single cell analysis of M. tuberculosis phenotype and macrophage lineages in the infected lung

In this study, we detail a novel approach that combines bacterial fitness fluorescent reporter strains with scRNA-seq to simultaneously acquire the host transcriptome, surface marker expression, and bacterial phenotype for each infected cell. This approach facilitates the dissection of the functional heterogeneity of M. tuberculosis-infected alveolar (AMs) and interstitial macrophages (IMs) in vivo. We identify clusters of pro-inflammatory AMs associated with stressed bacteria, in addition to three different populations of IMs with heterogeneous bacterial phenotypes. Finally, we show that the main macrophage populations in the lung are epigenetically constrained in their response to infection, while inter-species comparison reveals that most AMs subsets are conserved between mice and humans. This conceptual approach is readily transferable to other infectious disease agents with the potential for an increased understanding of the roles that different host cell populations play during the course of an infection.

Best practices on the differential expression analysis of multi-species RNA-seq

Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

Dual transcriptional analysis reveals adaptation of host and pathogen to intracellular survival of Pseudomonas aeruginosa associated with urinary tract infection

Long-term survival of bacterial pathogens during persistent bacterial infections can be associated with antibiotic treatment failure and poses a serious public health problem. Infections caused by the Gram-negative pathogen Pseudomonas aeruginosa, which can cause both acute and chronic infections, are particularly challenging due to its high intrinsic resistance to antibiotics. The ineffectiveness of antibiotics is exacerbated when bacteria reside intracellularly within host cells where they can adopt a drug tolerant state. While the early steps of adherence and entry of P. aeruginosa into mammalian cells have been described, the subsequent fate of internalized bacteria, as well as host and bacterial molecular pathways facilitating bacterial long-term survival, are not well defined. In particular, long-term survival within bladder epithelial cells has not been demonstrated and this may have important implications for the understanding and treatment of UTIs caused by P. aeruginosa. Here, we demonstrate and characterize the intracellular survival of wild type (WT) P. aeruginosa inside bladder epithelial cells and a mutant with a disruption in the bacterial two-component regulator AlgR that is unable to survive intracellularly. Using simultaneous dual RNA-seq transcriptional profiling, we define the transcriptional response of intracellular bacteria and their corresponding invaded host cells. The bacterial transcriptional response demonstrates that WT bacteria rapidly adapt to the stress encountered in the intracellular environment in contrast to ΔalgR bacteria. Analysis of the host transcriptional response to invasion suggests that the NF-κB signaling pathway, previously shown to be required for extracellular bacterial clearance, is paradoxically also required for intracellular bacterial survival. Lastly, we demonstrate that intracellular survival is important for pathogenesis of P. aeruginosa in vivo using a model of murine urinary tract infection. We propose that the unappreciated ability of P. aeruginosa to survive intracellularly may play an important role in contributing to the chronicity and recurrence of P. aeruginosa in urinary tract infections.

Chronic persistent bacterial infections are a serious and growing public health problem worsened by the rise in antibiotic resistance, yet new approaches for treating these infections are lacking. These long-term infections can occur when bacteria invade and survive inside host cells where they can hide from the immune system and become less susceptible to killing by antibiotics. Pseudomonas aeruginosa, a bacterium conventionally considered an extracellular pathogen, can cause chronic infections of many organ systems, including the urinary tract. Here, we show that P. aeruginosa can in fact survive inside bladder epithelial cells and becomes tolerant to antibiotic treatment. Using gene expression analysis, we show that bacteria quickly adapt to the intracellular environment while the corresponding host cells upregulate the NF-κB signaling pathway. We demonstrate that this response, which had previously been shown to be required for clearance of extracellular bacteria, is paradoxically also required for survival of intracellular bacteria. We propose that the ability of P. aeruginosa to survive intracellularly plays an important role in contributing to the chronicity and recurrence of P. aeruginosa infections and that targeting host pathways, such as NF-κB signaling, could transform our ability to manage chronic and/or recurrent infections.

These Are the Genes You're Looking For: Finding Host Resistance Genes

Humanity's ongoing struggle with new, re-emerging and endemic infectious diseases serves as a frequent reminder of the need to understand host-pathogen interactions. Recent advances in genomics have dramatically advanced our understanding of how genetics contributes to host resistance or susceptibility to bacterial infection. Here we discuss current trends in defining host-bacterial interactions at the genome-wide level, including screens that harness CRISPR/Cas9 genome editing, natural genetic variation, proteomics, and transcriptomics. We report on the merits, limitations, and findings of these innovative screens and discuss their complementary nature. Finally, we speculate on future innovation as we continue to progress through the postgenomic era and towards deeper mechanistic insight and clinical applications.

Cross-species RNA-seq for deciphering host-microbe interactions

The human body is constantly exposed to microorganisms, which entails manifold interactions between human cells and diverse commensal or pathogenic bacteria. The cellular states of the interacting cells are decisive for the outcome of these encounters such as whether bacterial virulence programmes and host defence or tolerance mechanisms are induced. This Review summarizes how next-generation RNA sequencing (RNA-seq) has become a primary technology to study host-microbe interactions with high resolution, improving our understanding of the physiological consequences and the mechanisms at play. We illustrate how the discriminatory power and sensitivity of RNA-seq helps to dissect increasingly complex cellular interactions in time and space down to the single-cell level. We also outline how future transcriptomics may answer currently open questions in host-microbe interactions and inform treatment schemes for microbial disorders.

Evolution of Drug-Resistant Mycobacterium tuberculosis Strains and Their Adaptation to the Human Lung Environment

In the last two decades, multi (MDR), extensively (XDR), extremely (XXDR) and total (TDR) drug-resistant Mycobacterium tuberculosis (M.tb) strains have emerged as a threat to public health worldwide, stressing the need to develop new tuberculosis (TB) prevention and treatment strategies. It is estimated that in the next 35 years, drug-resistant TB will kill around 75 million people and cost the global economy $16.7 trillion. Indeed, the COVID-19 pandemic alone may contribute with the development of 6.3 million new TB cases due to lack of resources and enforced confinement in TB endemic areas. Evolution of drug-resistant M.tb depends on numerous factors, such as bacterial fitness, strain's genetic background and its capacity to adapt to the surrounding environment, as well as host-specific and environmental factors. Whole-genome transcriptomics and genome-wide association studies in recent years have shed some insights into the complexity of M.tb drug resistance and have provided a better understanding of its underlying molecular mechanisms. In this review, we will discuss M.tb phenotypic and genotypic changes driving resistance, including changes in cell envelope components, as well as recently described intrinsic and extrinsic factors promoting resistance emergence and transmission. We will further explore how drug-resistant M.tb adapts differently than drug-susceptible strains to the lung environment at the cellular level, modulating M.tb-host interactions and disease outcome, and novel next generation sequencing (NGS) strategies to study drug-resistant TB.

Single-cell RNA-seq reveals CD16- monocytes as key regulators of human monocyte transcriptional response to Toxoplasma

Monocytes are among the major myeloid cells that respond to Toxoplasma, a ubiquitous foodborne that infects ≥ 1 billion people worldwide, in human peripheral blood. As such, a molecular understanding of human monocyte-Toxoplasma interactions can expedite the development of novel human toxoplasmosis control strategies. Current molecular studies on monocyte-Toxoplasma interactions are based on average cell or parasite responses across bulk cell populations. Although informative, population-level averages of monocyte responses to Toxoplasma have sometimes produced contradictory results, such as whether CCL2 or IL12 define effective monocyte responses to the parasite. Here, we used single-cell dual RNA sequencing (scDual-Seq) to comprehensively define, for the first time, the monocyte and parasite transcriptional responses that underpin human monocyte-Toxoplasma encounters at the single cell level. We report extreme transcriptional variability between individual monocytes. Furthermore, we report that Toxoplasma-exposed and unexposed monocytes are transcriptionally distinguished by a reactive subset of CD14⁺CD16^- monocytes. Functional cytokine assays on sorted monocyte populations show that the infection-distinguishing monocytes secrete high levels of chemokines, such as CCL2 and CXCL5. These findings uncover the Toxoplasma-induced monocyte transcriptional heterogeneity and shed new light on the cell populations that largely define cytokine and chemokine secretion in human monocytes exposed to Toxoplasma.

Advances and challenges in single-cell RNA-seq of microbial communities

Microbes have developed complex strategies to respond to their environment and escape the immune system by individualizing their behavior. While single-cell RNA sequencing has become instrumental for studying mammalian cells, its use with fungi, protozoa and bacteria is still in its infancy. In this review, we highlight the major progress towards mapping the molecular states of microbes at the single-cell level using genome-wide transcriptomics and describe how these technologies can be extended to probe thousands of species at high throughput. We envision that mammalian and microbial single-cell profiling could soon be integrated for the study of microbial communities in health and disease.

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.

Host-Microbiome Interactions in the Era of Single-Cell Biology

Microbes are the most prevalent form of life yet also the least well-understood in terms of their diversity. Due to a greater appreciation of their role in modulating host physiology, microbes have come to the forefront of biological investigation of human health and disease. Despite this, capturing the heterogeneity of microbes, and that of the host responses they induce, has been challenging due to the bulk methods of nucleic acid and cellular analysis. One of the greatest recent advancements in our understanding of complex organisms has happened in the field of single-cell analysis through genomics, transcriptomics, and spatial resolution. While significantly advancing our understanding of host biology, these techniques have only recently been applied to microbial systems to shed light on their diversity as well as interactions with host cells in both commensal and pathogenic contexts. In this review, we highlight emerging technologies that are poised to provide key insights into understanding how microbe heterogeneity can be studied. We then take a detailed look into how host single-cell analysis has uncovered the impact of microbes on host heterogeneity and the effect of host biology on microorganisms. Most of these insights would have been challenging, and in some cases impossible, without the advent of single-cell analysis, suggesting the importance of the single-cell paradigm for progressing the microbiology field forward through a host-microbiome perspective and applying these insights to better understand and treat human disease.

Innate Immune Mechanisms to Protect Against Infection at the Human Decidual-Placental Interface

During pregnancy, the placenta forms the anatomical barrier between the mother and developing fetus. Infectious agents can potentially breach the placental barrier resulting in pathogenic transmission from mother to fetus. Innate immune responses, orchestrated by maternal and fetal cells at the decidual-placental interface, are the first line of defense to avoid vertical transmission. Here, we outline the anatomy of the human placenta and uterine lining, the decidua, and discuss the potential capacity of pathogen pattern recognition and other host defense strategies present in the innate immune cells at the placental-decidual interface. We consider major congenital infections that access the placenta from hematogenous or decidual route. Finally, we highlight the challenges in studying human placental responses to pathogens and vertical transmission using current experimental models and identify gaps in knowledge that need to be addressed. We further propose novel experimental strategies to address such limitations.

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.

Mapping Cellular Coordinates through Advances in Spatial Transcriptomics Technology

Complex cell-to-cell communication underlies the basic processes essential for homeostasis in the given tissue architecture. Obtaining quantitative gene-expression of cells in their native context has significantly advanced through single-cell RNA sequencing technologies along with mechanical and enzymatic tissue manipulation. This approach, however, is largely reliant on the physical dissociation of individual cells from the tissue, thus, resulting in a library with unaccounted positional information. To overcome this, positional information can be obtained by integrating imaging and positional barcoding. Collectively, spatial transcriptomics strategies provide tissue architecture-dependent as well as position-dependent cellular functions. This review discusses the current technologies for spatial transcriptomics ranging from the methods combining mechanical dissociation and single-cell RNA sequencing to computational spatial re-mapping.

For the Greater (Bacterial) Good: Heterogeneous Expression of Energetically Costly Virulence Factors

Bacterial populations are phenotypically heterogeneous, which allows subsets of cells to survive and thrive following changes in environmental conditions. For bacterial pathogens, changes within the host environment occur over the course of the immune response to infection and can result in exposure to host-derived, secreted antimicrobials or force direct interactions with immune cells. Many recent studies have shown host cell interactions promote virulence factor expression, forcing subsets of bacterial cells to battle the host response, while other bacteria reap the benefits of this pacification. It still remains unclear whether virulence factor expression is truly energetically costly within host tissues and whether expression is sufficient to impact the growth kinetics of virulence factor-expressing cells. However, it is clear that slow-growing subsets of bacteria emerge during infection and that these subsets are particularly difficult to eliminate with antibiotics. This minireview will focus on our current understanding of heterogenous virulence factor expression and discuss the evidence that supports or refutes the hypothesis that virulence factor expression is linked to slowed growth and antibiotic tolerance.

Hybridization-based capture of pathogen mRNA enables paired host-pathogen transcriptional analysis

Dual transcriptional profiling of host and bacteria during infection is challenging due to the low abundance of bacterial mRNA. We report Pathogen Hybrid Capture (PatH-Cap), a method to enrich for bacterial mRNA and deplete bacterial rRNA simultaneously from dual RNA-seq libraries using transcriptome-specific probes. By addressing both the differential RNA content of the host relative to the infecting bacterium and the overwhelming abundance of uninformative structural RNAs (rRNA, tRNA) of both species in a single step, this approach enables analysis of very low-input RNA samples. By sequencing libraries before (pre-PatH-Cap) and after (post-PatH-Cap) enrichment, we achieve dual transcriptional profiling of host and bacteria, respectively, from the same sample. Importantly, enrichment preserves relative transcript abundance and increases the number of unique bacterial transcripts per gene in post-PatH-Cap libraries compared to pre-PatH-Cap libraries at the same sequencing depth, thereby decreasing the sequencing depth required to fully capture the transcriptional profile of the infecting bacteria. We demonstrate that PatH-Cap enables the study of low-input samples including single eukaryotic cells infected by 1-3 Pseudomonas aeruginosa bacteria and paired host-pathogen temporal gene expression analysis of Mycobacterium tuberculosis infecting macrophages. PatH-Cap can be applied to the study of a range of pathogens and microbial species, and more generally, to lowly-abundant species in mixed populations.

Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes

Understanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the eukaryotic tree of life. But we remain ignorant of the life cycles, physiology and cellular states of most of these microbial eukaryotes, as well as of their interactions with other organisms. Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology. First, we review different single-cell transcriptomics methodologies with particular focus on microbial eukaryote applications. Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches. Finally, we envision the application of single-cell transcriptomics to protist communities to interrogate not only community components, but also the gene expression signatures of distinct cellular and physiological states, as well as the transcriptional dynamics of interspecific interactions. Overall, we argue that single-cell transcriptomics can significantly contribute to our understanding of the biology of microbial eukaryotes. This article is part of a discussion meeting issue 'Single cell ecology'.

Early Transcriptional Landscapes of Chlamydia trachomatis-Infected Epithelial Cells at Single Cell Resolution

Chlamydia are Gram-negative obligate intracellular bacterial pathogens responsible for a variety of disease in humans and animals worldwide. Chlamydia trachomatis causes trachoma in disadvantaged populations, and is the most common bacterial sexually transmitted infection in humans, causing reproductive tract disease. Antibiotic therapy successfully treats diagnosed chlamydial infections, however asymptomatic infections are common. High-throughput transcriptomic approaches have explored chlamydial gene expression and infected host cell gene expression. However, these were performed on large cell populations, averaging gene expression profiles across all cells sampled and potentially obscuring biologically relevant subsets of cells. We generated a pilot dataset, applying single cell RNA-Seq (scRNA-Seq) to C. trachomatis infected and mock-infected epithelial cells to assess the utility, pitfalls and challenges of single cell approaches applied to chlamydial biology, and to potentially identify early host cell biomarkers of chlamydial infection. Two hundred sixty-four time-matched C. trachomatis-infected and mock-infected HEp-2 cells were collected and subjected to scRNA-Seq. After quality control, 200 cells were retained for analysis. Two distinct clusters distinguished 3-h cells from 6- and 12-h. Pseudotime analysis identified a possible infection-specific cellular trajectory for Chlamydia-infected cells, while differential expression analyses found temporal expression of metallothioneins and genes involved with cell cycle regulation, innate immune responses, cytoskeletal components, lipid biosynthesis and cellular stress. We find that changes to the host cell transcriptome at early times of C. trachomatis infection are readily discernible by scRNA-Seq, supporting the utility of single cell approaches to identify host cell biomarkers of chlamydial infection, and to further deconvolute the complex host response to infection.

Emerging Principles in Myelopoiesis at Homeostasis and during Infection and Inflammation

Myelopoiesis ensures the steady state of the myeloid cell compartment. Technological advances in fate mapping and genetic engineering, as well as the advent of single cell RNA-sequencing, have highlighted the heterogeneity of the hematopoietic system and revealed new concepts in myeloid cell ontogeny. These technologies are also shedding light on mechanisms of myelopoiesis at homeostasis and at different phases of infection and inflammation, illustrating important feedback loops between affected tissues and the bone marrow. We review these findings here and revisit principles in myelopoiesis in light of the evolving understanding of myeloid cell ontogeny and heterogeneity. We argue for the importance of system-wide evaluation of changes in myelopoiesis and discuss how even after the resolution of inflammation, long-lasting alterations in myelopoiesis may play a role in innate immune memory or trained immunity.

Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells

Complex interactions between different host immune cell types can determine the outcome of pathogen infections. Advances in single cell RNA-sequencing (scRNA-seq) allow probing of these immune interactions, such as cell-type compositions, which are then interpreted by deconvolution algorithms using bulk RNA-seq measurements. However, not all aspects of immune surveillance are represented by current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we develop a deconvolution algorithm for inferring cell-type specific infection responses from bulk measurements. We apply our dynamic deconvolution algorithm to a cohort of healthy individuals challenged ex vivo with Salmonella, and to three cohorts of tuberculosis patients during different stages of disease. We reveal cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and human infection outcomes.

Complex interactions between different host immune cell types can determine the outcome of pathogen infections. Here, Avraham and colleagues present a deconvolution algorithm that uses single-cell RNA and bulk RNA sequencing measurements of pathogen-infected cells to predict disease risk outcomes.

Single-Cell RNA Sequencing-Based Computational Analysis to Describe Disease Heterogeneity

The trillions of cells in the human body can be viewed as elementary but essential biological units that achieve different body states, but the low resolution of previous cell isolation and measurement approaches limits our understanding of the cell-specific molecular profiles. The recent establishment and rapid growth of single-cell sequencing technology has facilitated the identification of molecular profiles of heterogeneous cells, especially on the transcription level of single cells [single-cell RNA sequencing (scRNA-seq)]. As a novel method, the robustness of scRNA-seq under changing conditions will determine its practical potential in major research programs and clinical applications. In this review, we first briefly presented the scRNA-seq-related methods from the point of view of experiments and computation. Then, we compared several state-of-the-art scRNA-seq analysis frameworks mainly by analyzing their performance robustness on independent scRNA-seq datasets for the same complex disease. Finally, we elaborated on our hypothesis on consensus scRNA-seq analysis and summarized the potential indicative and predictive roles of individual cells in understanding disease heterogeneity by single-cell technologies.

Uncovering complex molecular networks in host-pathogen interactions using systems biology

Interactions between pathogens and their hosts can induce complex changes in both host and pathogen states to privilege pathogen survival or host clearance of the pathogen. To determine the consequences of specific host-pathogen interactions, a variety of techniques in microbiology, cell biology, and immunology are available to researchers. Systems biology that enables unbiased measurements of transcriptomes, proteomes, and other biomolecules has become increasingly common in the study of host-pathogen interactions. These approaches can be used to generate novel hypotheses or to characterize the effects of particular perturbations across an entire biomolecular network. With proper experimental design and complementary data analysis tools, high-throughput omics techniques can provide novel insights into the mechanisms that underlie processes from phagocytosis to pathogen immune evasion. Here, we provide an overview of the suite of biochemical approaches for high-throughput analyses of host-pathogen interactions, analytical frameworks for understanding the resulting datasets, and a vision for the future of this exciting field.