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PLoS Computational Biology Aug 2023Antibodies and humoral memory are key components of the adaptive immune system. We consider and computationally model mechanisms by which humoral memory present at...
Antibodies and humoral memory are key components of the adaptive immune system. We consider and computationally model mechanisms by which humoral memory present at baseline might increase rather than decrease infection load; we refer to this effect as EI-HM (enhancement of infection by humoral memory). We first consider antibody dependent enhancement (ADE) in which antibody enhances the growth of the pathogen, typically a virus, and typically at intermediate 'Goldilocks' levels of antibody. Our ADE model reproduces ADE in vitro and enhancement of infection in vivo from passive antibody transfer. But notably the simplest implementation of our ADE model never results in EI-HM. Adding complexity, by making the cross-reactive antibody much less neutralizing than the de novo generated antibody or by including a sufficiently strong non-antibody immune response, allows for ADE-mediated EI-HM. We next consider the possibility that cross-reactive memory causes EI-HM by crowding out a possibly superior de novo immune response. We show that, even without ADE, EI-HM can occur when the cross-reactive response is both less potent and 'directly' (i.e. independently of infection load) suppressive with regard to the de novo response. In this case adding a non-antibody immune response to our computational model greatly reduces or completely eliminates EI-HM, which suggests that 'crowding out' is unlikely to cause substantial EI-HM. Hence, our results provide examples in which simple models give qualitatively opposite results compared to models with plausible complexity. Our results may be helpful in interpreting and reconciling disparate experimental findings, especially from dengue, and for vaccination.
Topics: Antibodies, Neutralizing; Cross Reactions; Vaccination
PubMed: 37603552
DOI: 10.1371/journal.pcbi.1011377 -
Frontiers in Molecular Neuroscience 2023Advances in genome sequencing technologies have favored the identification of rare mutations linked to neurological disorders in humans. Recently, a autosomal dominant... (Review)
Review
Advances in genome sequencing technologies have favored the identification of rare mutations linked to neurological disorders in humans. Recently, a autosomal dominant mutation in was identified (NM_052876.3: c.892C > T, NP_443108.1; p.Arg298Trp), associated with severe neurological symptoms including intellectual disability, microcephaly, and epilepsy. As had never before been associated with neurological diseases, we investigated how this mutation might lead to altered brain function. We examined neurotransmission in autaptic glutamatergic mouse neurons expressing the murine homolog of the human mutant NACC1, i.e., Nacc1-R284W. We observed that expression of Nacc1-R284W impaired glutamatergic neurotransmission in a cell-autonomous manner, likely through a dominant negative mechanism. Furthermore, by screening for Nacc1 interaction targets in the brain, we identified SynGAP1, GluK2A, and several SUMO E3 ligases as novel Nacc1 interaction partners. At a biochemical level, Nacc1-R284W exhibited reduced binding to SynGAP1 and GluK2A, and also showed greatly increased SUMOylation. Ablating the SUMOylation of Nacc1-R284W partially restored its interaction with SynGAP1 but did not restore binding to GluK2A. Overall, these data indicate a role for Nacc1 in regulating glutamatergic neurotransmission, which is substantially impaired by the expression of a disease-associated Nacc1 mutant. This study provides the first functional insights into potential deficits in neuronal function in patients expressing the mutant NACC1 protein.
PubMed: 37533751
DOI: 10.3389/fnmol.2023.1115880 -
Frontiers in Behavioral Neuroscience 2023Epilepsy is characterized by recurrent unprovoked seizures. Mutations in the voltage-gated sodium channel alpha subunit 1 () gene are the main monogenic cause of...
BACKGROUND
Epilepsy is characterized by recurrent unprovoked seizures. Mutations in the voltage-gated sodium channel alpha subunit 1 () gene are the main monogenic cause of epilepsy. Type and location of variants make a huge difference in the severity of disorder, ranging from the mild phenotype (genetic epilepsy with febrile seizures plus, GEFS+) to the severe phenotype (developmental and epileptic encephalopathies, DEEs). Dravet Syndrome (DS) is an infantile-onset DEE, characterized by drug-resistant epilepsy and temperature sensitivity or febrile seizures. Genetic test results reveal variants are positive in 80% DS patients and DS is mainly caused by variants.
METHODS
Trio-whole exome sequencing (WES) was used to detect variants which were associated with clinical phenotype of five probands with epilepsy or twitching. Then, Sanger sequencing was performed to validate the five novel variants and segregation analysis. After analyzing the location of five variants, the pathogenic potential was assessed.
RESULTS
In this study, we identified five novel variants (c.4224G > C, c.3744_3752del, c.209del, c.5727_5734delTTTAAAACinsCTTAAAAAG and c.5776delT) as the causative variants. In the five novel variants, four were and the remaining one was inherited. All novel variants would be classified as "pathogenic" or "likely pathogenic."
CONCLUSION
The five novel variants will enrich the mutations database and provide the corresponding reference data for the further genetic counseling.
PubMed: 38025388
DOI: 10.3389/fnbeh.2023.1272748 -
ELife Nov 2023Invariant natural-killer T (NKT) cells play pathogenic roles in allergic asthma in murine models and possibly also humans. While many studies show that the development...
Invariant natural-killer T (NKT) cells play pathogenic roles in allergic asthma in murine models and possibly also humans. While many studies show that the development and functions of innate and adaptive immune cells depend on their metabolic state, the evidence for this in NKT cells is very limited. It is also not clear whether such metabolic regulation of NKT cells could participate in their pathogenic activities in asthma. Here, we showed that acetyl-coA-carboxylase 1 (ACC1)-mediated de novo fatty-acid synthesis is required for the survival of NKT cells and their deleterious functions in allergic asthma. ACC1, which is a key fatty-acid synthesis enzyme, was highly expressed by lung NKT cells from WT mice that were developing asthma. -Cre:: mice failed to develop OVA-induced and HDM-induced asthma. Moreover, NKT cell-deficient mice that were reconstituted with ACC1-deficient NKT cells failed to develop asthma, unlike when WT NKT cells were transferred. ACC1 deficiency in NKT cells associated with reduced expression of fatty acid-binding proteins (FABPs) and peroxisome proliferator-activated receptor (PPAR)γ, but increased glycolytic capacity that promoted NKT-cell death. Furthermore, circulating NKT cells from allergic-asthma patients expressed higher and levels than the corresponding cells from non-allergic-asthma patients and healthy individuals. Thus, de novo fatty-acid synthesis prevents NKT-cell death via an ACC1-FABP-PPARγ axis, which contributes to their homeostasis and their pathogenic roles in allergic asthma.
Topics: Humans; Animals; Mice; Natural Killer T-Cells; Respiratory Hypersensitivity; Asthma; Homeostasis; Cell Death
PubMed: 37917548
DOI: 10.7554/eLife.87536 -
Microbiome Research Reports 2023Comparative metagenomic analysis requires measuring a pairwise similarity between metagenomes in the dataset. Reference-based methods that compute a beta-diversity...
Comparative metagenomic analysis requires measuring a pairwise similarity between metagenomes in the dataset. Reference-based methods that compute a beta-diversity distance between two metagenomes are highly dependent on the quality and completeness of the reference database, and their application on less studied microbiota can be challenging. On the other hand, comparative metagenomic methods only rely on the sequence composition of metagenomes to compare datasets. While each one of these approaches has its strengths and limitations, their comparison is currently limited. We developed sets of simulated short-reads metagenomes to (1) compare k-mer-based and taxonomy-based distances and evaluate the impact of technical and biological variables on these metrics and (2) evaluate the effect of k-mer sketching and filtering. We used a real-world metagenomic dataset to provide an overview of the currently available tools for metagenomic comparative analysis. Using simulated metagenomes of known composition and controlled error rate, we showed that k-mer-based distance metrics were well correlated to the taxonomic distance metric for quantitative Beta-diversity metrics, but the correlation was low for presence/absence distances. The community complexity in terms of taxa richness and the sequencing depth significantly affected the quality of the k-mer-based distances, while the impact of low amounts of sequence contamination and sequencing error was limited. Finally, we benchmarked currently available comparative metagenomic tools and compared their output on two datasets of fecal metagenomes and showed that most k-mer-based tools were able to recapitulate the data structure observed using taxonomic approaches. This study expands our understanding of the strength and limitations of k-mer-based comparative metagenomic approaches and aims to provide concrete guidelines for researchers interested in applying these approaches to their metagenomic datasets.
PubMed: 38058765
DOI: 10.20517/mrr.2023.26 -
ArXiv Apr 2024Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Diffusion models currently achieve state of the art...
Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Diffusion models currently achieve state of the art performance for 3D molecule generation. In this work, we explore the use of flow matching, a recently proposed generative modeling framework that generalizes diffusion models, for the task of de novo molecule generation. Flow matching provides flexibility in model design; however, the framework is predicated on the assumption of continuously-valued data. 3D de novo molecule generation requires jointly sampling continuous and categorical variables such as atom position and atom type. We extend the flow matching framework to categorical data by constructing flows that are constrained to exist on a continuous representation of categorical data known as the probability simplex. We call this extension SimplexFlow. We explore the use of SimplexFlow for de novo molecule generation. However, we find that, in practice, a simpler approach that makes no accommodations for the categorical nature of the data yields equivalent or superior performance. As a result of these experiments, we present FlowMol, a flow matching model for 3D de novo generative model that achieves improved performance over prior flow matching methods, and we raise important questions about the design of prior distributions for achieving strong performance in flow matching models. Code and trained models for reproducing this work are available at https://github.com/dunni3/FlowMol.
PubMed: 38745704
DOI: No ID Found -
PloS One 2024Patterns of single nucleotide polymorphisms (SNPs) in eukaryotic DNA are traditionally attributed to selective pressure, drift, identity descent, or related...
Patterns of single nucleotide polymorphisms (SNPs) in eukaryotic DNA are traditionally attributed to selective pressure, drift, identity descent, or related factors-without accounting for ways in which bias during de novo SNP formation, itself, might contribute. A functional and phenotypic analysis based on evolutionary resilience of DNA points to decreased numbers of non-synonymous SNPs in human and other genomes, with a predominant component of SNP depletion in the human gene pool caused by robust preferences during de novo SNP formation (rather than selective constraint). Ramifications of these findings are broad, belie a number of concepts regarding human evolution, and point to a novel interpretation of evolving DNA across diverse species.
Topics: Polymorphism, Single Nucleotide; Humans; Evolution, Molecular; Genome, Human; Animals; Genome; Genomics
PubMed: 38753830
DOI: 10.1371/journal.pone.0303257 -
Frontiers in Immunology 2023Antibody mediated rejection (ABMR) is a major factor limiting outcome after organ transplantation. Anti-HLA donor-specific antibodies (DSA) of the IgG isotype are mainly...
INTRODUCTION
Antibody mediated rejection (ABMR) is a major factor limiting outcome after organ transplantation. Anti-HLA donor-specific antibodies (DSA) of the IgG isotype are mainly responsible for ABMR. Recently DSA of the IgE isotype were demonstrated in murine models as well as in a small cohort of sensitized transplant recipients. In the present study, we aimed to determine the frequency of pre-existing and anti-HLA IgE antibodies in a cohort of 105 solid organ transplant recipients.
METHODS
We prospectively measured anti-HLA IgE antibodies in a cohort of kidney (n=60), liver, heart and lung (n=15 each) transplant recipients before and within one-year after transplantation, employing a single-antigen bead assay for HLA class I and class II antigens. Functional activity of anti-HLA IgE antibodies was assessed by an mediator release assay. Antibodies of the IgG1-4 subclasses and Th1 and Th2 cytokines were measured in anti-HLA IgE positive patients.
RESULTS
Pre-existing anti-HLA IgE antibodies were detected in 10% of renal recipients (including 3.3% IgE-DSA) and in 4.4% of non-renal solid organ transplant recipients (heart, liver and lung cohort). Anti-HLA IgE occurred only in patients that were positive for anti-HLA IgG, and most IgE positive patients had had a previous transplant. Only a small fraction of patients developed anti-HLA IgE antibodies (1.7% of kidney recipients and 4.4% of non-renal recipients), whereas no IgE-DSA was detected. IgG subclass antibodies showed a distinct pattern in patients who were positive for anti-HLA IgE. Moreover, patients with anti-HLA IgE showed elevated Th2 and also Th1 cytokine levels. Serum from IgE positive recipients led to degranulation of basophils , demonstrating functionality of anti-HLA IgE.
DISCUSSION
These data demonstrate that anti-HLA IgE antibodies occur at low frequency in kidney, liver, heart and lung transplant recipients. Anti-HLA IgE development is associated with sensitization at the IgG level, in particular through previous transplants and distinct IgG subclasses. Taken together, HLA specific IgE sensitization is a new phenomenon in solid organ transplant recipients whose potential relevance for allograft injury requires further investigation.
Topics: Humans; Animals; Mice; Prospective Studies; Liver; Heart Transplantation; Kidney; Immunosuppressive Agents; Antilymphocyte Serum; Immunoglobulin G; Lung; Immunoglobulin E
PubMed: 37731514
DOI: 10.3389/fimmu.2023.1179036 -
Discover Oncology Jun 2024Hepatocellular carcinoma (HCC), an aggressive malignancy with a dismal prognosis, poses a significant public health challenge. Recent research has highlighted the... (Review)
Review
Hepatocellular carcinoma (HCC), an aggressive malignancy with a dismal prognosis, poses a significant public health challenge. Recent research has highlighted the crucial role of lipid metabolism in HCC development, with enhanced lipid synthesis and uptake contributing to the rapid proliferation and tumorigenesis of cancer cells. Lipids, primarily synthesized and utilized in the liver, play a critical role in the pathological progression of various cancers, particularly HCC. Cancer cells undergo metabolic reprogramming, an essential adaptation to the tumor microenvironment (TME), with fatty acid metabolism emerging as a key player in this process. This review delves into intricate interplay between HCC and lipid metabolism, focusing on four key areas: de novo lipogenesis, fatty acid oxidation, dysregulated lipid metabolism of immune cells in the TME, and therapeutic strategies targeting fatty acid metabolism for HCC treatment.
PubMed: 38833109
DOI: 10.1007/s12672-024-01069-y -
JAMA Network Open Sep 2023Despite recent breakthroughs in therapy, advanced lung cancer still poses a therapeutic challenge. The survival profile of patients with metastatic lung cancer remains...
IMPORTANCE
Despite recent breakthroughs in therapy, advanced lung cancer still poses a therapeutic challenge. The survival profile of patients with metastatic lung cancer remains poorly understood by metastatic disease type (ie, de novo stage IV vs distant recurrence).
OBJECTIVE
To evaluate the association of metastatic disease type on overall survival (OS) among patients with non-small cell lung cancer (NSCLC) and to identify potential mechanisms underlying any survival difference.
DESIGN, SETTING, AND PARTICIPANTS
Cohort study of a national US population based at a tertiary referral center in the San Francisco Bay Area using participant data from the National Lung Screening Trial (NLST) who were enrolled between 2002 and 2004 and followed up for up to 7 years as the primary cohort and patient data from Stanford Healthcare (SHC) for diagnoses between 2009 and 2019 and followed up for up to 13 years as the validation cohort. Participants from NLST with de novo metastatic or distant recurrent NSCLC diagnoses were included. Data were analyzed from January 2021 to March 2023.
EXPOSURES
De novo stage IV vs distant recurrent metastatic disease.
MAIN OUTCOMES AND MEASURES
OS after diagnosis of metastatic disease.
RESULTS
The NLST and SHC cohort consisted of 660 and 180 participants, respectively (411 men [62.3%] vs 109 men [60.6%], 602 White participants [91.2%] vs 111 White participants [61.7%], and mean [SD] age of 66.8 [5.5] vs 71.4 [7.9] years at metastasis, respectively). Patients with distant recurrence showed significantly better OS than patients with de novo metastasis (adjusted hazard ratio [aHR], 0.72; 95% CI, 0.60-0.87; P < .001) in NLST, which was replicated in SHC (aHR, 0.64; 95% CI, 0.43-0.96; P = .03). In SHC, patients with de novo metastasis more frequently progressed to the bone (63 patients with de novo metastasis [52.5%] vs 19 patients with distant recurrence [31.7%]) or pleura (40 patients with de novo metastasis [33.3%] vs 8 patients with distant recurrence [13.3%]) than patients with distant recurrence and were primarily detected through symptoms (102 patients [85.0%]) as compared with posttreatment surveillance (47 patients [78.3%]) in the latter. The main finding remained consistent after further adjusting for metastasis sites and detection methods.
CONCLUSIONS AND RELEVANCE
In this cohort study, patients with distant recurrent NSCLC had significantly better OS than those with de novo disease, and the latter group was associated with characteristics that may affect overall survival. This finding can help inform future clinical trial designs to ensure a balance for baseline patient characteristics.
Topics: Male; Humans; Child; Carcinoma, Non-Small-Cell Lung; Lung Neoplasms; Cohort Studies; Health Facilities; Patients
PubMed: 37751203
DOI: 10.1001/jamanetworkopen.2023.35813