Helmholtz Institute for RNA-based Infection Research

With the advent of next generation sequencing methods and progress in transcriptome analysis, it became obvious that the human genome contains much more than just protein-coding genes. In fact, up to 70% of our genome is transcribed into RNA that does not serve as templates for proteins. In this review, we focus on the emerging roles of these long non-coding RNAs (lncRNAs) in the field of tumor biology. Long ncRNAs were found to be deregulated in several human cancers and show tissue-specific expression. Functional studies revealed a broad spectrum of mechanisms applied by lncRNAs such as HOTAIR, MALAT1, ANRIL or lincRNA-p21 to fulfill their functions. Here, we link the cellular processes influenced by long ncRNAs to the hallmarks of cancer and therefore provide an ncRNA point-of-view on tumor biology. This should stimulate new research directions and therapeutic options considering long ncRNAs as novel prognostic markers and therapeutic targets.

The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.

Rationale: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they have been defined by the expression of a restricted number of markers. Objective: We have applied single-cell RNA sequencing as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. Method and Results: We performed single-cell RNA sequencing of total aortic CD45 + cells extracted from the nondiseased (chow fed) and atherosclerotic (11 weeks of high-fat diet) aorta of low-density lipoprotein receptor–deficient ( Ldlr −/− ) mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortas, whereas monocytes, monocyte-derived dendritic cells, and 2 populations of macrophages were almost exclusively detectable in atherosclerotic aortas, comprising inflammatory macrophages showing enrichment in Il1b and previously undescribed TREM2 hi (triggered receptor expressed on myeloid cells 2) macrophages showing enrichment in Trem2 . Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these 3 macrophage subsets and monocyte-derived dendritic cells and uncovered putative functions of each cell type. Notably, TREM2 hi macrophages seemed to be endowed with specialized functions in lipid metabolism and catabolism and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe −/− aortas, indicating relevance of our findings in different stages of atherosclerosis and mouse models. Conclusions: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and monocyte-derived dendritic cells in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.

Abstract Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine 1,2 . Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes 3 . However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation 4,5 . Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.

Fusobacterium nucleatum is an oral anaerobe recently found to be prevalent in human colorectal cancer (CRC) where it is associated with poor treatment outcome. In mice, hematogenous F. nucleatum can colonize CRC tissue using its lectin Fap2, which attaches to tumor-displayed Gal-GalNAc. Here, we show that Gal-GalNAc levels increase as human breast cancer progresses, and that occurrence of F. nucleatum gDNA in breast cancer samples correlates with high Gal-GalNAc levels. We demonstrate Fap2-dependent binding of the bacterium to breast cancer samples, which is inhibited by GalNAc. Intravascularly inoculated Fap2-expressing F. nucleatum ATCC 23726 specifically colonize mice mammary tumors, whereas Fap2-deficient bacteria are impaired in tumor colonization. Inoculation with F. nucleatum suppresses accumulation of tumor infiltrating T cells and promotes tumor growth and metastatic progression, the latter two of which can be counteracted by antibiotic treatment. Thus, targeting F. nucleatum or Fap2 might be beneficial during treatment of breast cancer.

Rationale: Atherosclerosis is a chronic inflammatory disease that is driven by the interplay of pro- and anti-inflammatory leukocytes in the aorta. Yet, the phenotypic and transcriptional diversity of aortic leukocytes is poorly understood. Objective: We characterized leukocytes from healthy and atherosclerotic mouse aortas in-depth by single-cell RNA-sequencing and mass cytometry (cytometry by time of flight) to define an atlas of the immune cell landscape in atherosclerosis. Methods and Results: Using single-cell RNA-sequencing of aortic leukocytes from chow diet– and Western diet–fed Apoe −/− and Ldlr −/− mice, we detected 11 principal leukocyte clusters with distinct phenotypic and spatial characteristics while the cellular repertoire in healthy aortas was less diverse. Gene set enrichment analysis on the single-cell level established that multiple pathways, such as for lipid metabolism, proliferation, and cytokine secretion, were confined to particular leukocyte clusters. Leukocyte populations were differentially regulated in atherosclerotic Apoe −/− and Ldlr −/− mice. We confirmed the phenotypic diversity of these clusters with a novel mass cytometry 35-marker panel with metal-labeled antibodies and conventional flow cytometry. Cell populations retrieved by these protein-based approaches were highly correlated to transcriptionally defined clusters. In an integrated screening strategy of single-cell RNA-sequencing, mass cytometry, and fluorescence-activated cell sorting, we detected 3 principal B-cell subsets with alterations in surface markers, functional pathways, and in vitro cytokine secretion. Leukocyte cluster gene signatures revealed leukocyte frequencies in 126 human plaques by a genetic deconvolution strategy. This approach revealed that human carotid plaques and microdissected mouse plaques were mostly populated by macrophages, T-cells, and monocytes. In addition, the frequency of genetically defined leukocyte populations in carotid plaques predicted cardiovascular events in patients. Conclusions: The definition of leukocyte diversity by high-dimensional analyses enables a fine-grained analysis of aortic leukocyte subsets, reveals new immunologic mechanisms and cell-type–specific pathways, and establishes a functional relevance for lesional leukocytes in human atherosclerosis.

It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications. In this Review, several experts discuss progress in the decade since the development of transposon-based approaches for bacterial genetic screens. They describe how advances in both experimental technologies and analytical strategies are resulting in insights into diverse biological processes.

The metastasis-associated lung adenocarcinoma transcript 1, MALAT1, is a long non-coding RNA (lncRNA) that has been discovered as a marker for lung cancer metastasis. It is highly abundant, its expression is strongly regulated in many tumor entities including lung adenocarcinoma and hepatocellular carcinoma as well as physiological processes, and it is associated with many RNA binding proteins and highly conserved throughout evolution. The nuclear transcript MALAT-1 has been functionally associated with gene regulation and alternative splicing and its regulation has been shown to impact proliferation, apoptosis, migration and invasion. Here, we have developed a human and a mouse knockout system to study the loss-of-function phenotypes of this important ncRNA. In human tumor cells, MALAT1 expression was abrogated using Zinc Finger Nucleases. Unexpectedly, the quantitative loss of MALAT1 did neither affect proliferation nor cell cycle progression nor nuclear architecture in human lung or liver cancer cells. Moreover, genetic loss of Malat1 in a knockout mouse model did not give rise to any obvious phenotype or histological abnormalities in Malat1-null compared with wild-type animals. Thus, loss of the abundant nuclear long ncRNA MALAT1 is compatible with cell viability and normal development.

Actively persistent Salmonella A proportion of Salmonella cells can enter a reversible state of growth arrest, which allows them to tolerate environmental stress such as antibiotics. Stapels et al. found that these cells are not dormant but are actively modulating their environment. Salmonella within their host macrophage niche deployed a specialized type 3 secretory system called SPI-2 to deliver virulence factors, including SteE, into host cells. SteE changed the cytokine profile of the infected macrophages to reprogram them into a noninflammatory and infection-permissive state. Thus, when antibiotics were removed, the Salmonella could reemerge and cause disease. Science , this issue p. 1156

Characterizing the interactions that SARS-CoV-2 viral RNAs make with host cell proteins during infection can improve our understanding of viral RNA functions and the host innate immune response. Using RNA antisense purification and mass spectrometry, we identified up to 104 human proteins that directly and specifically bind to SARS-CoV-2 RNAs in infected human cells. We integrated the SARS-CoV-2 RNA interactome with changes in proteome abundance induced by viral infection and linked interactome proteins to cellular pathways relevant to SARS-CoV-2 infections. We demonstrated by genetic perturbation that cellular nucleic acid-binding protein (CNBP) and La-related protein 1 (LARP1), two of the most strongly enriched viral RNA binders, restrict SARS-CoV-2 replication in infected cells and provide a global map of their direct RNA contact sites. Pharmacological inhibition of three other RNA interactome members, PPIA, ATP1A1, and the ARP2/3 complex, reduced viral replication in two human cell lines. The identification of host dependency factors and defence strategies as presented in this work will improve the design of targeted therapeutics against SARS-CoV-2.

The ever-expanding set of CRISPR technologies and their programmable RNA-guided nucleases exhibit remarkable flexibility in DNA targeting. However, this flexibility comes with an ever-present constraint: the requirement for a protospacer adjacent motif (PAM) flanking each target. While PAMs play an essential role in self/nonself discrimination by CRISPR-Cas immune systems, this constraint has launched a far-reaching expedition for nucleases with relaxed PAM requirements. Here, we review ongoing efforts toward realizing PAM-free nucleases through natural ortholog mining and protein engineering. We also address potential consequences of fully eliminating PAM recognition and instead propose an alternative nuclease repertoire covering all possible PAM sequences.

The transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables "dual RNA-seq" studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique.

Understanding RNA processing and turnover requires knowledge of cleavages by major endoribonucleases within a living cell. We have employed TIER-seq (transiently inactivating an endoribonuclease followed by RNA-seq) to profile cleavage products of the essential endoribonuclease RNase E in Salmonella enterica. A dominating cleavage signature is the location of a uridine two nucleotides downstream in a single-stranded segment, which we rationalize structurally as a key recognition determinant that may favor RNase E catalysis. Our results suggest a prominent biogenesis pathway for bacterial regulatory small RNAs whereby RNase E acts together with the RNA chaperone Hfq to liberate stable 3' fragments from various precursor RNAs. Recapitulating this process in vitro, Hfq guides RNase E cleavage of a representative small-RNA precursor for interaction with a mRNA target. In vivo, the processing is required for target regulation. Our findings reveal a general maturation mechanism for a major class of post-transcriptional regulators.

A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13)C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential.

Rationale: After myocardial infarction, neutrophils rapidly and massively infiltrate the heart, where they promote both tissue healing and damage. Objective: To characterize the dynamics of circulating and cardiac neutrophil diversity after infarction. Methods and results: We employed single-cell transcriptomics combined with cell surface epitope detection by sequencing to investigate temporal neutrophil diversity in the blood and heart after murine myocardial infarction. At day 1, 3, and 5 after infarction, cardiac Ly6G + (lymphocyte antigen 6G) neutrophils could be delineated into 6 distinct clusters with specific time-dependent patterning and proportions. At day 1, neutrophils were characterized by a gene expression profile proximal to bone marrow neutrophils ( Cd177 , Lcn2 , Fpr1 ), and putative activity of transcriptional regulators involved in hypoxic response ( Hif1a ) and emergency granulopoiesis ( Cebpb ). At 3 and 5 days, 2 major subsets of Siglecf hi (enriched for eg, Icam1 and Tnf ) and Siglecf low ( Slpi, Ifitm1 ) neutrophils were found. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) analysis in blood and heart revealed that while circulating neutrophils undergo a process of aging characterized by loss of surface CD62L and upregulation of Cxcr4 , heart infiltrating neutrophils acquired a unique SiglecF hi signature. SiglecF hi neutrophils were absent from the bone marrow and spleen, indicating local acquisition of the SiglecF hi signature. Reducing the influx of blood neutrophils by anti-Ly6G treatment increased proportions of cardiac SiglecF hi neutrophils, suggesting accumulation of locally aged neutrophils. Computational analysis of ligand/receptor interactions revealed putative pathways mediating neutrophil to macrophage communication in the myocardium. Finally, SiglecF hi neutrophils were also found in atherosclerotic vessels, revealing that they arise across distinct contexts of cardiovascular inflammation. Conclusions: Altogether, our data provide a time-resolved census of neutrophil diversity and gene expression dynamics in the mouse blood and ischemic heart at the single-cell level, and reveal a process of local tissue specification of neutrophils in the ischemic heart characterized by the acquisition of a SiglecF hi signature.

T cells and plasma levels of complement proteins upstream of C3a were associated with fatal outcome of COVID-19, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19.

Abstract Many evolutionarily distant pathogenic organisms have evolved similar survival strategies to evade the immune responses of their hosts. These include antigenic variation, through which an infecting organism prevents clearance by periodically altering the identity of proteins that are visible to the immune system of the host 1 . Antigenic variation requires large reservoirs of immunologically diverse antigen genes, which are often generated through homologous recombination, as well as mechanisms to ensure the expression of one or very few antigens at any given time. Both homologous recombination and gene expression are affected by three-dimensional genome architecture and local DNA accessibility 2,3 . Factors that link three-dimensional genome architecture, local chromatin conformation and antigenic variation have, to our knowledge, not yet been identified in any organism. One of the major obstacles to studying the role of genome architecture in antigenic variation has been the highly repetitive nature and heterozygosity of antigen-gene arrays, which has precluded complete genome assembly in many pathogens. Here we report the de novo haplotype-specific assembly and scaffolding of the long antigen-gene arrays of the model protozoan parasite Trypanosoma brucei , using long-read sequencing technology and conserved features of chromosome folding 4 . Genome-wide chromosome conformation capture (Hi-C) reveals a distinct partitioning of the genome, with antigen-encoding subtelomeric regions that are folded into distinct, highly compact compartments. In addition, we performed a range of analyses—Hi-C, fluorescence in situ hybridization, assays for transposase-accessible chromatin using sequencing and single-cell RNA sequencing—that showed that deletion of the histone variants H3.V and H4.V increases antigen-gene clustering, DNA accessibility across sites of antigen expression and switching of the expressed antigen isoform, via homologous recombination. Our analyses identify histone variants as a molecular link between global genome architecture, local chromatin conformation and antigenic variation.

The last few decades have led to an explosion in our understanding of the major roles that small regulatory RNAs (sRNAs) play in regulatory circuits and the responses to stress in many bacterial species. Much of the foundational work was carried out with Escherichia coli and Salmonella enterica serovar Typhimurium. The studies of these organisms provided an overview of how the sRNAs function and their impact on bacterial physiology, serving as a blueprint for sRNA biology in many other prokaryotes. They also led to the development of new technologies. In this chapter, we first summarize how these sRNAs were identified, defining them in the process. We discuss how they are regulated and how they act and provide selected examples of their roles in regulatory circuits and the consequences of this regulation. Throughout, we summarize the methodologies that were developed to identify and study the regulatory RNAs, most of which are applicable to other bacteria. Newly updated databases of the known sRNAs in E. coli K-12 and S. enterica Typhimurium SL1344 serve as a reference point for much of the discussion and, hopefully, as a resource for readers and for future experiments to address open questions raised in this review.

MicroRNAs are small RNAs that post-transcriptionally regulate eukaryotic gene expression. In addition to their involvement in a wide range of physiological and pathological processes, including viral infections, microRNAs are increasingly implicated in the eukaryotic response to bacterial pathogens. Recent studies have characterized changes in host microRNA expression following infection with exclusively extracellular (Helicobacter pylori) or intracellular (Salmonella enterica) Gram-negative bacteria, as well as in the response to Gram-positive (Listeria monocytogenes) and other pathogens (Mycobacterium and Francisella species). In this review, we discuss the emerging roles of microRNAs in mammalian host signaling and defense against bacterial pathogens.

Peptide antibiotics are an abundant and synthetically tractable source of molecular diversity, but they are often cationic and can be cytotoxic, nephrotoxic and/or ototoxic, which has limited their clinical development. Here we report structure-guided optimization of an amphipathic peptide, arenicin-3, originally isolated from the marine lugworm Arenicola marina. The peptide induces bacterial membrane permeability and ATP release, with serial passaging resulting in a mutation in mlaC, a phospholipid transport gene. Structure-based design led to AA139, an antibiotic with broad-spectrum in vitro activity against multidrug-resistant and extensively drug-resistant bacteria, including ESBL, carbapenem- and colistin-resistant clinical isolates. The antibiotic induces a 3-4 log reduction in bacterial burden in mouse models of peritonitis, pneumonia and urinary tract infection. Cytotoxicity and haemolysis of the progenitor peptide is ameliorated with AA139, and the 'no observable adverse effect level' (NOAEL) dose in mice is ~10-fold greater than the dose generally required for efficacy in the infection models.