Can Small Molecules Provide Clues on Disease Progression in Cerebrospinal Fluid from Mild Cognitive Impairment and Alzheimer's Disease Patients?

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease, which is currently diagnosed via clinical symptoms and nonspecific biomarkers (such as Aß1-42, t-Tau, and p-Tau) measured in cerebrospinal fluid (CSF), which alone do not provide sufficient insights into disease progression. In this pilot study, these biomarkers were complemented with small-molecule analysis using non-target high-resolution mass spectrometry coupled with liquid chromatography (LC) on the CSF of three groups: AD, mild cognitive impairment (MCI) due to AD, and a non-demented (ND) control group. An open-source cheminformatics pipeline based on MS-DIAL and patRoon was enhanced using CSF- and AD-specific suspect lists to assist in data interpretation. Chemical Similarity Enrichment Analysis revealed a significant increase of hydroxybutyrates in AD, including 3-hydroxybutanoic acid, which was found at higher levels in AD compared to MCI and ND. Furthermore, a highly sensitive target LC-MS method was used to quantify 35 bile acids (BAs) in the CSF, revealing several statistically significant differences including higher dehydrolithocholic acid levels and decreased conjugated BA levels in AD. This work provides several promising small-molecule hypotheses that could be used to help track the progression of AD in CSF samples.

Immune Activation in Alzheimer Disease.

Alzheimer disease (AD) is the most common neurodegenerative disease, and with no efficient curative treatment available, its medical, social, and economic burdens are expected to dramatically increase. AD is historically characterized by amyloid ß (Aß) plaques and tau neurofibrillary tangles, but over the last 25 years chronic immune activation has been identified as an important factor contributing to AD pathogenesis. In this article, we review recent and important advances in our understanding of the significance of immune activation in the development of AD. We describe how brain-resident macrophages, the microglia, are able to detect Aß species and be activated, as well as the consequences of activated microglia in AD pathogenesis. We discuss transcriptional changes of microglia in AD, their unique heterogeneity in humans, and emerging strategies to study human microglia. Finally, we expose, beyond Aß and microglia, the role of peripheral signals and different cell types in immune activation.

Mitophagy in Alzheimer's disease: Molecular defects and therapeutic approaches.

Mitochondrial dysfunctions are central players in Alzheimer's disease (AD). In addition, impairments in mitophagy, the process of selective mitochondrial degradation by autophagy leading to a gradual accumulation of defective mitochondria, have also been reported to occur in AD. We provide an updated overview of the recent discoveries and advancements on mitophagic molecular dysfunctions in AD-derived fluids and cells as well as in AD brains. We discuss studies using AD cellular and animal models that have unraveled the contribution of relevant AD-related proteins (Tau, Aß, APP-derived fragments and APOE) in mitophagy failure. In accordance with the important role of impaired mitophagy in AD, we report on various therapeutic strategies aiming at stimulating mitophagy in AD and we summarize the benefits of these potential therapeutic strategies in human clinical trials.

CALDERA: finding all significant de Bruijn subgraphs for bacterial GWAS.

MOTIVATION: Genome-wide association studies (GWAS), aiming to find genetic variants associated with a trait, have widely been used on bacteria to identify genetic determinants of drug resistance or hypervirulence. Recent bacterial GWAS methods usually rely on k-mers, whose presence in a genome can denote variants ranging from single-nucleotide polymorphisms to mobile genetic elements. This approach does not require a reference genome, making it easier to account for accessory genes. However, a same gene can exist in slightly different versions across different strains, leading to diluted effects. RESULTS: Here, we overcome this issue by testing covariates built from closed connected subgraphs (CCSs) of the de Bruijn graph defined over genomic k-mers. These covariates capture polymorphic genes as a single entity, improving k-mer-based GWAS both in terms of power and interpretability. However, a method naively testing all possible subgraphs would be powerless due to multiple testing corrections, and the mere exploration of these subgraphs would quickly become computationally intractable. The concept of testable hypothesis has successfully been used to address both problems in similar contexts. We leverage this concept to test all CCSs by proposing a novel enumeration scheme for these objects which fully exploits the pruning opportunity offered by testability, resulting in drastic improvements in computational efficiency. Our method integrates with existing visual tools to facilitate interpretation. AVAILABILITY AND IMPLEMENTATION: We provide an implementation of our method, as well as code to reproduce all results at https://github.com/HectorRDB/Caldera_ISMB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Totoro: Identifying Active Reactions During the Transient State for Metabolic Perturbations.

Motivation: The increasing availability of metabolomic data and their analysis are improving the understanding of cellular mechanisms and how biological systems respond to different perturbations. Currently, there is a need for novel computational methods that facilitate the analysis and integration of increasing volume of available data. Results: In this paper, we present Totoro a new constraint-based approach that integrates quantitative non-targeted metabolomic data of two different metabolic states into genome-wide metabolic models and predicts reactions that were most likely active during the transient state. We applied Totoro to real data of three different growth experiments (pulses of glucose, pyruvate, succinate) from Escherichia coli and we were able to predict known active pathways and gather new insights on the different metabolisms related to each substrate. We used both the E. coli core and the iJO1366 models to demonstrate that our approach is applicable to both smaller and larger networks. Availability: Totoro is an open source method (available at https://gitlab.inria.fr/erable/totoro) suitable for any organism with an available metabolic model. It is implemented in C++ and depends on IBM CPLEX which is freely available for academic purposes.

Efficiently sparse listing of classes of optimal cophylogeny reconciliations.

BACKGROUND: Cophylogeny reconciliation is a powerful method for analyzing host-parasite (or host-symbiont) co-evolution. It models co-evolution as an optimization problem where the set of all optimal solutions may represent different biological scenarios which thus need to be analyzed separately. Despite the significant research done in the area, few approaches have addressed the problem of helping the biologist deal with the often huge space of optimal solutions. RESULTS: In this paper, we propose a new approach to tackle this problem. We introduce three different criteria under which two solutions may be considered biologically equivalent, and then we propose polynomial-delay algorithms that enumerate only one representative per equivalence class (without listing all the solutions). CONCLUSIONS: Our results are of both theoretical and practical importance. Indeed, as shown by the experiments, we are able to significantly reduce the space of optimal solutions while still maintaining important biological information about the whole space.

Bidirectional genome-wide CRISPR screens reveal host factors regulating SARS-CoV-2, MERS-CoV and seasonal coronaviruses

Several genome-wide CRISPR knockout screens have been conducted to identify host factors regulating SARS-CoV-2 replication, but the models used have often relied on overexpression of ACE2 receptor. Additionally, such screens have yet to identify the protease TMPRSS2, known to be important for viral entry at the plasma membrane. Here, we conducted a meta-analysis of these screens and showed a high level of cell-type specificity of the identified hits, arguing for the necessity of additional models to uncover the full landscape of SARS-CoV-2 host factors. We performed genome-wide knockout and activation CRISPR screens in Calu-3 lung epithelial cells, as well as knockout screens in Caco-2 intestinal cells. In addition to identifying ACE2 and TMPRSS2 as top hits, our study reveals a series of so far unidentified and critical host-dependency factors, including the Adaptins AP1G1 and AP1B1 and the flippase ATP8B1. Moreover, new anti-SARS-CoV-2 proteins with potent activity, including several membrane-associated Mucins, IL6R, and CD44 were identified. We further observed that these genes mostly acted at the critical step of viral entry, with the notable exception of ATP8B1, the knockout of which prevented late stages of viral replication. Exploring the pro- and anti-viral breadth of these genes using highly pathogenic MERS-CoV, seasonal HCoV-NL63 and -229E and influenza A orthomyxovirus, we reveal that some genes such as AP1G1 and ATP8B1 are general coronavirus cofactors. In contrast, Mucins recapitulated their known role as a general antiviral defense mechanism. These results demonstrate the value of considering multiple cell models and perturbational modalities for understanding SARS-CoV-2 replication and provide a list of potential new targets for therapeutic interventions.

Accumulation of amyloid precursor protein C-terminal fragments triggers mitochondrial structure, function, and mitophagy defects in Alzheimer's disease models and human brains.

Several lines of recent evidence indicate that the amyloid precursor protein-derived C-terminal fragments (APP-CTFs) could correspond to an etiological trigger of Alzheimer's disease (AD) pathology. Altered mitochondrial homeostasis is considered an early event in AD development. However, the specific contribution of APP-CTFs to mitochondrial structure, function, and mitophagy defects remains to be established. Here, we demonstrate in neuroblastoma SH-SY5Y cells expressing either APP Swedish mutations, or the ß-secretase-derived APP-CTF fragment (C99) combined with ß- and γ-secretase inhibition, that APP-CTFs accumulation independently of Aß triggers excessive mitochondrial morphology alteration (i.e., size alteration and cristae disorganization) associated with enhanced mitochondrial reactive oxygen species production. APP-CTFs accumulation also elicit basal mitophagy failure illustrated by enhanced conversion of LC3, accumulation of LC3-I and/or LC3-II, non-degradation of SQSTM1/p62, inconsistent Parkin and PINK1 recruitment to mitochondria, enhanced levels of membrane and matrix mitochondrial proteins, and deficient fusion of mitochondria with lysosomes. We confirm the contribution of APP-CTFs accumulation to morphological mitochondria alteration and impaired basal mitophagy in vivo in young 3xTgAD transgenic mice treated with γ-secretase inhibitor as well as in adeno-associated-virus-C99 injected mice. Comparison of aged 2xTgAD and 3xTgAD mice indicates that, besides APP-CTFs, an additional contribution of Aß to late-stage mitophagy activation occurs. Importantly, we report on mitochondrial accumulation of APP-CTFs in human post-mortem sporadic AD brains correlating with mitophagy failure molecular signature. Since defective mitochondria homeostasis plays a pivotal role in AD pathogenesis, targeting mitochondrial dysfunctions and/or mitophagy by counteracting early APP-CTFs accumulation may represent relevant therapeutic interventions in AD.

Molecular Dysfunctions of Mitochondria-Associated Membranes (MAMs) in Alzheimer's Disease.

Alzheimer's disease (AD) is a multifactorial neurodegenerative pathology characterized by a progressive decline of cognitive functions. Alteration of various signaling cascades affecting distinct subcellular compartment functions and their communication likely contribute to AD progression. Among others, the alteration of the physical association between the endoplasmic reticulum (ER) and mitochondria, also reffered as mitochondria-associated membranes (MAMs), impacts various cellular housekeeping functions such as phospholipids-, glucose-, cholesterol-, and fatty-acid-metabolism, as well as calcium signaling, which are all altered in AD. Our review describes the physical and functional proteome crosstalk between the ER and mitochondria and highlights the contribution of distinct molecular components of MAMs to mitochondrial and ER dysfunctions in AD progression. We also discuss potential strategies targeting MAMs to improve mitochondria and ER functions in AD.

A genome-wide CRISPR/Cas9 knock-out screen identifies the DEAD box RNA helicase DDX42 as a broad antiviral inhibitor

Genome-wide screens are powerful approaches to unravel new regulators of viral infections. Here, we used a CRISPR/Cas9 screen to reveal new HIV-1 inhibitors. This approach led us to identify the RNA helicase DDX42 as an intrinsic antiviral inhibitor. DDX42 was previously described as a non-processive helicase, able to bind RNA secondary structures such as G-quadruplexes, with no clearly defined function ascribed. Our data show that depletion of endogenous DDX42 significantly increased HIV-1 DNA accumulation and infection in cell lines and primary cells. DDX42 overexpression inhibited HIV-1, whereas a dominant-negative mutant increased infection. Importantly, DDX42 also restricted retrotransposition of LINE-1, infection with other retroviruses and positive-strand RNA viruses, including CHIKV and SARS-CoV-2. However, DDX42 did not inhibit infection with three negative-strand RNA viruses, arguing against a general, unspecific effect on target cells, which was confirmed by RNA-seq analysis. DDX42 was found in the vicinity of viral elements by proximity ligation assays, and cross-linking RNA immunoprecipitation confirmed a specific interaction of DDX42 with RNAs from sensitive viruses. This strongly suggested a direct mode of action of DDX42 on viral ribonucleoprotein complexes. Taken together, our results show for the first time a new and important role of DDX42 in intrinsic antiviral immunity.

SARS-CoV-2 replication triggers an MDA-5-dependent interferon production which is unable to efficiently control replication

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third highly pathogenic coronavirus to spill over to humans in less than 20 years, after SARS-CoV-1 in 2002-2003 and Middle East respiratory syndrome (MERS)-CoV in 2012. SARS-CoV-2 is the etiologic agent of coronavirus disease 19 (COVID-19), which ranges from mild respiratory symptoms to severe lung injury and death in the most severe cases. The COVID-19 pandemic is currently a major health issue worldwide. Immune dysregulation characterized by altered innate cytokine responses is thought to contribute to the pathology of COVID-19 patients, which is a testimony of the fundamental role of the innate immune response against SARS-CoV-2. Here, we further characterized the host cell antiviral response against SARS-CoV-2 by using primary human airway epithelia and immortalized model cell lines. We mainly focused on the type I and III interferon (IFN) responses, which lead to the establishment of an antiviral state through the expression of IFN-stimulated genes (ISGs). Our results demonstrate that both primary airway epithelial cells and model cell lines elicit a robust immune response characterized by a strong induction of type I and III IFN through the detection of viral pathogen molecular patterns (PAMPs) by melanoma differentiation associated gene (MDA)-5. However, despite the high levels of type I and III IFNs produced in response to SARS-CoV-2 infection, the IFN response was unable to control viral replication, whereas IFN pre-treatment strongly inhibited viral replication and de novo production of infectious virions. Taken together, these results highlight the complex and ambiguous interplay between viral replication and the timing of IFN responses.

Algorithms for the quantitative Lock/Key model of cytoplasmic incompatibility.

Cytoplasmic incompatibility (CI) relates to the manipulation by the parasite Wolbachia of its host reproduction. Despite its widespread occurrence, the molecular basis of CI remains unclear and theoretical models have been proposed to understand the phenomenon. We consider in this paper the quantitative Lock-Key model which currently represents a good hypothesis that is consistent with the data available. CI is in this case modelled as the problem of covering the edges of a bipartite graph with the minimum number of chain subgraphs. This problem is already known to be NP-hard, and we provide an exponential algorithm with a non trivial complexity. It is frequent that depending on the dataset, there may be many optimal solutions which can be biologically quite different among them. To rely on a single optimal solution may therefore be problematic. To this purpose, we address the problem of enumerating (listing) all minimal chain subgraph covers of a bipartite graph and show that it can be solved in quasi-polynomial time. Interestingly, in order to solve the above problems, we considered also the problem of enumerating all the maximal chain subgraphs of a bipartite graph and improved on the current results in the literature for the latter. Finally, to demonstrate the usefulness of our methods we show an application on a real dataset.

Capybara: equivalence ClAss enumeration of coPhylogenY event-BAsed ReconciliAtions.

MOTIVATION: Phylogenetic tree reconciliation is the method of choice in analyzing host-symbiont systems. Despite the many reconciliation tools that have been proposed in the literature, two main issues remain unresolved: (i) listing suboptimal solutions (i.e. whose score is 'close' to the optimal ones) and (ii) listing only solutions that are biologically different 'enough'. The first issue arises because the optimal solutions are not always the ones biologically most significant; providing many suboptimal solutions as alternatives for the optimal ones is thus very useful. The second one is related to the difficulty to analyze an often huge number of optimal solutions. In this article, we propose Capybara that addresses both of these problems in an efficient way. Furthermore, it includes a tool for visualizing the solutions that significantly helps the user in the process of analyzing the results. AVAILABILITY AND IMPLEMENTATION: The source code, documentation and binaries for all platforms are freely available at https://capybara-doc.readthedocs.io/. CONTACT: yishu.wang@univ-lyon1.fr or blerina.sinaimeri@inria.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOOMIN - Mathematical explOration of 'Omics data on a MetabolIc Network.

MOTIVATION: Analysis of differential expression of genes is often performed to understand how the metabolic activity of an organism is impacted by a perturbation. However, because the system of metabolic regulation is complex and all changes are not directly reflected in the expression levels, interpreting these data can be difficult. RESULTS: In this work, we present a new algorithm and computational tool that uses a genome-scale metabolic reconstruction to infer metabolic changes from differential expression data. Using the framework of constraint-based analysis, our method produces a qualitative hypothesis of a change in metabolic activity. In other words, each reaction of the network is inferred to have increased, decreased, or remained unchanged in flux. In contrast to similar previous approaches, our method does not require a biological objective function and does not assign on/off activity states to genes. An implementation is provided and it is available online. We apply the method to three published datasets to show that it successfully accomplishes its two main goals: confirming or rejecting metabolic changes suggested by differentially expressed genes based on how well they fit in as parts of a coordinated metabolic change, as well as inferring changes in reactions whose genes did not undergo differential expression. AVAILABILITY AND IMPLEMENTATION: github.com/htpusa/moomin. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Upregulation of the Sarco-Endoplasmic Reticulum Calcium ATPase 1 Truncated Isoform Plays a Pathogenic Role in Alzheimer's Disease.

Dysregulation of the Endoplasmic Reticulum (ER) Ca2+ homeostasis and subsequent ER stress activation occur in Alzheimer Disease (AD). We studied the contribution of the human truncated isoform of the sarco-endoplasmic reticulum Ca2+ ATPase 1 (S1T) to AD. We examined S1T expression in human AD-affected brains and its functional consequences in cellular and transgenic mice AD models. S1T expression is increased in sporadic AD brains and correlates with amyloid ß (Aß) and ER stress chaperone protein levels. Increased S1T expression was also observed in human neuroblastoma cells expressing Swedish-mutated ß-amyloid precursor protein (ßAPP) or treated with Aß oligomers. Lentiviral overexpression of S1T enhances in return the production of APP C-terminal fragments and Aß through specific increases of ß-secretase expression and activity, and triggers neuroinflammation. We describe a molecular interplay between S1T-dependent ER Ca2+ leak, ER stress and ßAPP-derived fragments that could contribute to AD setting and/or progression.

A Combinatorial Algorithm for Microbial Consortia Synthetic Design.

Synthetic biology has boomed since the early 2000s when it started being shown that it was possible to efficiently synthetize compounds of interest in a much more rapid and effective way by using other organisms than those naturally producing them. However, to thus engineer a single organism, often a microbe, to optimise one or a collection of metabolic tasks may lead to difficulties when attempting to obtain a production system that is efficient, or to avoid toxic effects for the recruited microorganism. The idea of using instead a microbial consortium has thus started being developed in the last decade. This was motivated by the fact that such consortia may perform more complicated functions than could single populations and be more robust to environmental fluctuations. Success is however not always guaranteed. In particular, establishing which consortium is best for the production of a given compound or set thereof remains a great challenge. This is the problem we address in this paper. We thus introduce an initial model and a method that enable to propose a consortium to synthetically produce compounds that are either exogenous to it, or are endogenous but where interaction among the species in the consortium could improve the production line.