An Integrative Framework Reveals Signaling-to-Transcription Events in Toll-like Receptor Signaling

An HIV-1 CRISPR-Cas9 membrane trafficking screen reveals a role for PICALM intersecting endolysosomes and immunity

HIV-1 hijacks host proteins involved in membrane trafficking, endocytosis, and autophagy that are critical for virus replication. Molecular details are lacking but are essential to inform on the development of alternative antiviral strategies. Despite their potential as clinical targets, only a few membrane trafficking proteins have been functionally characterized in HIV-1 replication. To further elucidate roles in HIV-1 replication, we performed a CRISPR-Cas9 screen on 140 membrane trafficking proteins. We identified phosphatidylinositol-binding clathrin assembly protein (PICALM) that influences not only infection dynamics but also CD4+ SupT1 biology. The knockout (KO) of PICALM inhibited viral entry. In CD4+ SupT1 T cells, KO cells exhibited defects in intracellular trafficking and increased abundance of intracellular Gag and significant alterations in autophagy, immune checkpoint PD-1 levels, and differentiation markers. Thus, PICALM modulates a variety of pathways that ultimately affect HIV-1 replication, underscoring the potential of PICALM as a future target to control HIV-1.

Atypical cofilin signaling drives dendritic cell migration through the extracellular matrix via nuclear deformation

To mount an adaptive immune response, dendritic cells must migrate to lymph nodes to present antigens to T cells. Critical to 3D migration is the nucleus, which is the size-limiting barrier for migration through the extracellular matrix. Here, we show that inflammatory activation of dendritic cells leads to the nucleus becoming spherically deformed and enables dendritic cells to overcome the typical 2- to 3-μm diameter limit for 3D migration through gaps in the extracellular matrix. We show that the nuclear shape change is partially attained through reduced cell adhesion, whereas improved 3D migration is achieved through reprogramming of the actin cytoskeleton. Specifically, our data point to a model whereby the phosphorylation of cofilin-1 at serine 41 drives the assembly of a cofilin-actomyosin ring proximal to the nucleus and enhances migration through 3D collagen gels. In summary, these data describe signaling events through which dendritic cells deform their nucleus and enhance their migratory capacity.

Predicting gene-level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework

The Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway integrates complex cytokine signals via a limited number of molecular components, inspiring numerous efforts to clarify the diversity and specificity of STAT transcription factor function. We developed a computational framework to make global cytokine-induced gene predictions from STAT phosphorylation dynamics, modeling macrophage responses to interleukin (IL)-6 and IL-10, which signal through common STATs, but with distinct temporal dynamics and contrasting functions. Our mechanistic-to-machine learning model identified cytokine-specific genes associated with late pSTAT3 time frames and a preferential pSTAT1 reduction upon JAK2 inhibition. We predicted and validated the impact of JAK2 inhibition on gene expression, identifying genes that were sensitive or insensitive to JAK2 variation. Thus, we successfully linked STAT signaling dynamics to gene expression to support future efforts targeting pathology-associated STAT-driven gene sets. This serves as a first step in developing multi-level prediction models to understand and perturb gene expression outputs from signaling systems. A record of this paper's transparent peer review process is included in the supplemental information.

Myristoylated, alanine-rich C-kinase substrate (MARCKS) regulates toll-like receptor 4 signaling in macrophages

MARCKS (myristoylated alanine-rich C-kinase substrate) is a membrane-associated protein expressed in many cell types, including macrophages. MARCKS is functionally implicated in cell adhesion, phagocytosis, and inflammation. LPS (lipopolysaccharide) triggers inflammation via TLR4 (toll-like receptor 4).The presence of MARCKS and the formation of phospho-MARCKS in various cell types have been described, but the role(s) of MARCKS in regulating macrophage functions remain unclear. We investigated the role of MARCKS in inflammation. Confocal microscopy revealed that MARCKS and phospho-MARCKS increased localization to endosomes and the Golgi apparatus upon LPS stimulation.CRISPR-CAS9 mediated knockout of MARCKS in macrophages downregulated the production of TNF and IL6, suggesting a role for MARCKS in inflammatory responses. Our comprehensive proteomics analysis together with real-time metabolic assays comparing LPS-stimulation of WT and MARCKS knock-out macrophages provided insights into the involvement of MARCKS in specific biological processes including innate immune response, inflammatory response, cytokine production, and molecular functions such as extracellularly ATP-gated cation channel activity, electron transfer activity and oxidoreductase activity, uncovering specific proteins involved in regulating MARCKS activity upon LPS stimulation. MARCKS appears to be a key regulator of inflammation whose inhibition might be beneficial for therapeutic intervention in inflammatory diseases.

Signaling is the pathway to macrophage function

Tissue and inflammatory contexts are well appreciated to shape macrophage function to promote health or disease. However, there has been minimal progress towards understanding how these contexts modify signaling-to-transcription networks. Integration of mechanistic modeling and data-driven approaches will be crucial for investigating how cell state impacts macrophage decision-making.

Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework

The JAK-STAT pathway integrates complex cytokine signals via a limited number of molecular components, inspiring numerous efforts to clarify the diversity and specificity of STAT transcription factor function. We developed a computational workflow to make global cytokine-induced gene predictions from STAT phosphorylation dynamics, modeling macrophage responses to IL-6 and IL-10, which signal through common STATs, but with distinct temporal dynamics and contrasting functions. Our mechanistic-to-machine learning model identified select cytokine-induced gene sets associated with late pSTAT3 timeframes and a preferential pSTAT1 reduction upon JAK2 inhibition. We predicted and validated the impact of JAK2 inhibition on gene expression, identifying dynamically regulated genes that were sensitive or insensitive to JAK2 variation. Thus, we successfully linked STAT signaling dynamics to gene expression to support future efforts targeting pathology-associated STAT-driven gene sets. This serves as a first step in developing multi-level prediction models to understand and perturb gene expression outputs from signaling systems.

An atlas of substrate specificities for the human serine/threonine kinome

Protein phosphorylation is one of the most widespread post-translational modifications in biology1,2. With advances in mass-spectrometry-based phosphoproteomics, 90,000 sites of serine and threonine phosphorylation have so far been identified, and several thousand have been associated with human diseases and biological processes3,4. For the vast majority of phosphorylation events, it is not yet known which of the more than 300 protein serine/threonine (Ser/Thr) kinases encoded in the human genome are responsible3. Here we used synthetic peptide libraries to profile the substrate sequence specificity of 303 Ser/Thr kinases, comprising more than 84% of those predicted to be active in humans. Viewed in its entirety, the substrate specificity of the kinome was substantially more diverse than expected and was driven extensively by negative selectivity. We used our kinome-wide dataset to computationally annotate and identify the kinases capable of phosphorylating every reported phosphorylation site in the human Ser/Thr phosphoproteome. For the small minority of phosphosites for which the putative protein kinases involved have been previously reported, our predictions were in excellent agreement. When this approach was applied to examine the signalling response of tissues and cell lines to hormones, growth factors, targeted inhibitors and environmental or genetic perturbations, it revealed unexpected insights into pathway complexity and compensation. Overall, these studies reveal the intrinsic substrate specificity of the human Ser/Thr kinome, illuminate cellular signalling responses and provide a resource to link phosphorylation events to biological pathways.

The microglial lysosomal system in Alzheimer's disease: Guardian against proteinopathy

Microglia, the brain-resident immune cells, play an essential role in the upkeep of brain homeostasis. They actively adapt into specific activation states based on cues from the microenvironment. One of these encompasses the activated response microglia (ARMs) phenotype. It arises along a healthy aging process and in a range of neurodegenerative diseases, including Alzheimer's disease (AD). As the phenotype is characterized by an increased lipid metabolism, phagocytosis rate, lysosomal protease content and secretion of neuroprotective agents, it leaves to reason that the phenotype is adapted in an attempt to restore homeostasis. This is important to the conundrum of inflammatory processes. Inflammation per se may not be deleterious; it is only when microglial reactions become chronic or the microglial subtype is made dysfunctional by (multiple) risk proteins with single-nucleotide polymorphisms that microglial involvement becomes deleterious instead of beneficial. Interestingly, the ARMs up- and downregulate many late-onset AD-associated risk factor genes, the products of which are particularly active in the endolysosomal system. Hence, in this review, we focus on how the endolysosomal system is placed at the crossroad of inflammation and microglial capacity to keep pace with degradation.

TIM-3 restrains anti-tumour immunity by regulating inflammasome activation

T cell immunoglobulin and mucin-containing molecule 3 (TIM-3), first identified as a molecule expressed on interferon-γ producing T cells1, is emerging as an important immune-checkpoint molecule, with therapeutic blockade of TIM-3 being investigated in multiple human malignancies. Expression of TIM-3 on CD8+ T cells in the tumour microenvironment is considered a cardinal sign of T cell dysfunction; however, TIM-3 is also expressed on several other types of immune cell, confounding interpretation of results following blockade using anti-TIM-3 monoclonal antibodies. Here, using conditional knockouts of TIM-3 together with single-cell RNA sequencing, we demonstrate the singular importance of TIM-3 on dendritic cells (DCs), whereby loss of TIM-3 on DCs-but not on CD4+ or CD8+ T cells-promotes strong anti-tumour immunity. Loss of TIM-3 prevented DCs from expressing a regulatory program and facilitated the maintenance of CD8+ effector and stem-like T cells. Conditional deletion of TIM-3 in DCs led to increased accumulation of reactive oxygen species resulting in NLRP3 inflammasome activation. Inhibition of inflammasome activation, or downstream effector cytokines interleukin-1β (IL-1β) and IL-18, completely abrogated the protective anti-tumour immunity observed with TIM-3 deletion in DCs. Together, our findings reveal an important role for TIM-3 in regulating DC function and underscore the potential of TIM-3 blockade in promoting anti-tumour immunity by regulating inflammasome activation.

Artemisinin inhibits TLR4 signaling by targeting co-receptor MD2 in microglial BV-2 cells and prevents lipopolysaccharide-induced blood-brain barrier leakage in mice

Artemisinin and its derivatives have been the frontline drugs for treating malaria. In addition to the antiparasitic effect, accumulating evidence shows that artemisinins can alleviate neuroinflammatory responses in the central nervous system (CNS). However, the precise mechanisms underlying their anti-neuroinflammatory effects are unclear. Herein we attempted to delineate the molecule target of artemisinin in microglia. In vitro protein intrinsic fluorescence titrations and saturation transfer difference (STD)-NMR showed the direct binding of artemisinin to Toll-like receptor TLR4 co-receptor MD2. Cellular thermal shift assay (CETSA) showed that artemisinin binding increased MD2 stability, which implies that artemisinin directly binds to MD2 in the cellular context. Artemisinin bound MD2 showed much less collapse during the molecular dynamic simulations, which supports the increased stability of MD2 upon artemisinin binding. Flow cytometry analysis showed artemisinin inhibited LPS-induced TLR4 dimerization and endocytosis in microglial BV-2 cells. Therefore, artemisinin was found to inhibit the TLR4-JNK signaling axis and block LPS-induced pro-inflammatory factors nitric oxide, IL-1β and TNF-α in BV-2 cells. Furthermore, artemisinin restored LPS-induced decrease of junction proteins ZO-1, Occludin and Claudin-5 in primary brain microvessel endothelial cells, and attenuated LPS-induced blood-brain barrier disruption in mice as assessed by Evans blue. In all, this study unambiguously adds MD2 as a direct binding target of artemisinin in its anti-neuroinflammatory function. The results also suggest that artemisinin could be repurposed as a potential therapeutic intervention for inflammatory CNS diseases.

Approaching complexity: systems biology and ms-based techniques to address immune signaling

INTRODUCTION

Studying immune signaling has been critical for our understanding of immunology, pathogenesis, cancer, and homeostasis. To enhance the breadth of the analysis, high throughput methods have been developed to survey multiple areas simultaneously, including transcriptomics, reporter assays, and ELISAs. While these techniques have been extremely informative, mass-spectrometry-based technologies have been gaining momentum and starting to be widely used in the studies of immune signaling and systems immunology.

AREAS COVERED

We present established proteomic methods that have been used to address immune signaling and discuss the new mass-spectrometry- based techniques of interest to the expanding field of systems immunology. Established and new proteomic methods and their applications discussed here include post-translational modification analysis, protein quantification, secretome analysis, and interactomics. In addition, we present developments in small molecule and metabolite analysis, mass spectrometry imaging, and single cell analysis. Finally, we discuss the role of multi-omic integration in aiding leading edge investigation.

EXPERT OPINION

In science, available techniques enhance the breadth and depth of the studies. By incorporating proteomic techniques and their innovative use, it will be possible to expand the current studies and to address novel questions at the forefront of scientific discovery.

Inferring the transcriptional regulatory mechanism of signal-dependent gene expression via an integrative computational approach

Eukaryotic transcription factors (TFs) coordinate different upstream signals to regulate the expression of their target genes. To unveil this regulatory network in B-cell receptor signaling, we developed a computational pipeline to systematically analyze the extracellular signal-regulated kinase (ERK)- and IκB kinase (IKK)-dependent transcriptome responses. We combined a bilinear regression method and kinetic modeling to identify the signal-to-TF and TF-to-gene dynamics, respectively. We input a set of time-course experimental data for B cells and concentrated on transcriptional activators. The results show that the combination of TFs differentially controlled by ERK and IKK could contribute divergent expression dynamics in orchestrating the B-cell response. Our findings provide insights into the regulatory mechanisms underlying signal-dependent gene expression in eukaryotic cells.

Cellular and pathophysiological consequences of Arp2/3 complex inhibition: role of inhibitory proteins and pharmacological compounds

The actin-related protein complex 2/3 (Arp2/3) generates branched actin networks important for many cellular processes such as motility, vesicular trafficking, cytokinesis, and intercellular junction formation and stabilization. Activation of Arp2/3 requires interaction with actin nucleation-promoting factors (NPFs). Regulation of Arp2/3 activity is achieved by endogenous inhibitory proteins through direct binding to Arp2/3 and competition with NPFs or by binding to Arp2/3-induced actin filaments and disassembly of branched actin networks. Arp2/3 inhibition has recently garnered more attention as it has been associated with attenuation of cancer progression, neurotoxic effects during drug abuse, and pathogen invasion of host cells. In this review, we summarize current knowledge on expression, inhibitory mechanisms and function of endogenous proteins able to inhibit Arp2/3 such as coronins, GMFs, PICK1, gadkin, and arpin. Moreover, we discuss cellular consequences of pharmacological Arp2/3 inhibition.

Dynamics of Dual Specificity Phosphatases and Their Interplay with Protein Kinases in Immune Signaling

Dual specificity phosphatases (DUSPs) have a well-known role as regulators of the immune response through the modulation of mitogen-activated protein kinases (MAPKs). Yet the precise interplay between the various members of the DUSP family with protein kinases is not well understood. Recent multi-omics studies characterizing the transcriptomes and proteomes of immune cells have provided snapshots of molecular mechanisms underlying innate immune response in unprecedented detail. In this study, we focus on deciphering the interplay between members of the DUSP family with protein kinases in immune cells using publicly available omics datasets. Our analysis resulted in the identification of potential DUSP-mediated hub proteins including MAPK7, MAPK8, AURKA, and IGF1R. Furthermore, we analyzed the association of DUSP expression with TLR4 signaling and identified VEGF, FGFR, and SCF-KIT pathway modules to be regulated by the activation of TLR4 signaling. Finally, we identified several important kinases including LRRK2, MAPK8, and cyclin-dependent kinases as potential DUSP-mediated hubs in TLR4 signaling. The findings from this study have the potential to aid in the understanding of DUSP signaling in the context of innate immunity. Further, this will promote the development of therapeutic modalities for disorders with aberrant DUSP signaling.

Connectivity problems on heterogeneous graphs

BACKGROUND

Network connectivity problems are abundant in computational biology research, where graphs are used to represent a range of phenomena: from physical interactions between molecules to more abstract relationships such as gene co-expression. One common challenge in studying biological networks is the need to extract meaningful, small subgraphs out of large databases of potential interactions. A useful abstraction for this task turned out to be the Steiner Network problems: given a reference "database" graph, find a parsimonious subgraph that satisfies a given set of connectivity demands. While this formulation proved useful in a number of instances, the next challenge is to account for the fact that the reference graph may not be static. This can happen for instance, when studying protein measurements in single cells or at different time points, whereby different subsets of conditions can have different protein milieu.

RESULTS AND DISCUSSION

We introduce the condition Steiner Network problem in which we concomitantly consider a set of distinct biological conditions. Each condition is associated with a set of connectivity demands, as well as a set of edges that are assumed to be present in that condition. The goal of this problem is to find a minimal subgraph that satisfies all the demands through paths that are present in the respective condition. We show that introducing multiple conditions as an additional factor makes this problem much harder to approximate. Specifically, we prove that for C conditions, this new problem is NP-hard to approximate to a factor of C - ϵ , for every C ≥ 2 and ϵ > 0 , and that this bound is tight. Moving beyond the worst case, we explore a special set of instances where the reference graph grows monotonically between conditions, and show that this problem admits substantially improved approximation algorithms. We also developed an integer linear programming solver for the general problem and demonstrate its ability to reach optimality with instances from the human protein interaction network.

CONCLUSION

Our results demonstrate that in contrast to most connectivity problems studied in computational biology, accounting for multiplicity of biological conditions adds considerable complexity, which we propose to address with a new solver. Importantly, our results extend to several network connectivity problems that are commonly used in computational biology, such as Prize-Collecting Steiner Tree, and provide insight into the theoretical guarantees for their applications in a multiple condition setting.

Streamlined Protocol for Deep Proteomic Profiling of FAC-sorted Cells and Its Application to Freshly Isolated Murine Immune Cells

Proteomic profiling describes the molecular landscape of proteins in cells immediately available to sense, transduce, and enact the appropriate responses to extracellular queues. Transcriptional profiling has proven invaluable to our understanding of cellular responses; however, insights may be lost as mounting evidence suggests transcript levels only moderately correlate with protein levels in steady state cells. Mass spectrometry-based quantitative proteomics is a well-suited and widely used analytical tool for studying global protein abundances. Typical proteomic workflows are often limited by the amount of sample input that is required for deep and quantitative proteome profiling. This is especially true if the cells of interest need to be purified by fluorescence-activated cell sorting (FACS) and one wants to avoid ex vivo culturing. To address this need, we developed an easy to implement, streamlined workflow that enables quantitative proteome profiling from roughly 2 μg of protein input per experimental condition. Utilizing a combination of facile cell collection from cell sorting, solid-state isobaric labeling and multiplexing of peptides, and small-scale fractionation, we profiled the proteomes of 12 freshly isolated, primary murine immune cell types. Analyzing half of the 3e5 cells collected per cell type, we quantified over 7000 proteins across 12 key immune cell populations directly from their resident tissues. We show that low input proteomics is precise, and the data generated accurately reflects many aspects of known immunology, while expanding the list of cell-type specific proteins across the cell types profiled. The low input proteomics methods we developed are readily adaptable and broadly applicable to any cell or sample types and should enable proteome profiling in systems previously unattainable.

Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming

Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. We apply the method to reconstruct the landscape of reprogramming from 315,000 single-cell RNA sequencing (scRNA-seq) profiles, collected at half-day intervals across 18 days. The results reveal a wider range of developmental programs than previously characterized. Cells gradually adopt either a terminal stromal state or a mesenchymal-to-epithelial transition state. The latter gives rise to populations related to pluripotent, extra-embryonic, and neural cells, with each harboring multiple finer subpopulations. The analysis predicts transcription factors and paracrine signals that affect fates and experiments validate that the TF Obox6 and the cytokine GDF9 enhance reprogramming efficiency. Our approach sheds light on the process and outcome of reprogramming and provides a framework applicable to diverse temporal processes in biology.

Mass Spectrometry-based Structural Analysis and Systems Immunoproteomics Strategies for Deciphering the Host Response to Endotoxin

One cause of sepsis is systemic maladaptive immune response of the host to bacteria and specifically, to Gram-negative bacterial outer-membrane glycolipid lipopolysaccharide (LPS). On the host myeloid cell surface, proinflammatory LPS activates the innate immune system via Toll-like receptor-4/myeloid differentiation factor-2 complex. Intracellularly, LPS is also sensed by the noncanonical inflammasome through caspase-11 in mice and 4/5 in humans. The minimal functional determinant for innate immune activation is the membrane anchor of LPS called lipid A. Even subtle modifications to the lipid A scaffold can enable, diminish, or abolish immune activation. Bacteria are known to modify their LPS structure during environmental stress and infection of hosts to alter cellular immune phenotypes. In this review, we describe how mass spectrometry-based structural analysis of endotoxin helped uncover major determinations of molecular pathogenesis. Through characterization of LPS modifications, we now better understand resistance to antibiotics and cationic antimicrobial peptides, as well as how the environment impacts overall endotoxin structure. In addition, mass spectrometry-based systems immunoproteomics approaches can assist in elucidating the immune response against LPS. Many regulatory proteins have been characterized through proteomics and global/targeted analysis of protein modifications, enabling the discovery and characterization of novel endotoxin-mediated protein translational modifications.

Lipid bilayer stress in obesity-linked inflammatory and metabolic disorders

The maintenance of the characteristic lipid compositions and physicochemical properties of biological membranes is essential for their proper function. Mechanisms allowing to sense and restore membrane homeostasis have been identified in prokaryotes for a long time and more recently in eukaryotes. A membrane remodeling can result from aberrant metabolism as seen in obesity. In this review, we describe how such lipid bilayer stress can account for the modulation of membrane proteins involved in the pathogenesis of obesity-linked inflammatory and metabolic disorders. We address the case of the Toll-like receptor 4 that is implicated in the obesity-related low grade inflammation and insulin resistance. The lipid raft-mediated TLR4 activation is promoted by an enrichment of the plasma membrane with saturated lipids or cholesterol increasing the lipid phase order. We discuss of the plasma membrane Na, K-ATPase that illustrates a new concept according to which direct interactions between specific residues and particular lipids determine both stability and activity of the pump in parallel with indirect effects of the lipid bilayer. The closely related sarco(endo)-plasmic Ca-ATPase embedded in the more fluid ER membrane seems to be more sensitive to a lipid bilayer stress as demonstrated by its inactivation in cholesterol-loaded macrophages or its inhibition mediated by an increased PtdCho/PtdEtn ratio in obese mice hepatocytes. Finally, we describe the model recently proposed for the activation of the conserved IRE-1 protein through alterations in the ER membrane lipid packing and thickness. Such IRE-1 activation could occur in response to abnormal lipid synthesis and membrane remodeling as observed in hepatocytes exposed to excess nutrients. Since the IRE-1/XBP1 branch also stimulates the lipid synthesis, this pathway could create a vicious cycle "lipogenesis-ER lipid bilayer stress-lipogenesis" amplifying hepatic ER pathology and the obesity-linked systemic metabolic defects.