Cytopathic Mechanisms of HIV-1

The human immunodeficiency virus type 1 (HIV-1) has been intensely investigated since its discovery in 1983 as the cause of acquired immune deficiency syndrome (AIDS). With relatively few proteins made by the virus, it is able to accomplish many tasks, with each protein serving multiple functions. The Envelope glycoprotein, composed of the two noncovalently linked subunits, SU (surface glycoprotein) and TM (transmembrane glycoprotein) is largely responsible for host cell recognition and entry respectively. While the roles of the N-terminal residues of TM is well established as a fusion pore and anchor for Env into cell membranes, the role of the C-terminus of the protein is not well understood and is fiercely debated. This review gathers information on TM in an attempt to shed some light on the functional regions of this protein

Viroporin potential of the lentivirus lytic peptide (LLP) domains of the HIV-1 gp41 protein

<p>Abstract</p> <p>Background</p> <p>Mechanisms by which HIV-1 mediates reductions in CD4+ cell levels in infected persons are being intensely investigated, and have broad implications for AIDS drug and vaccine development. Virally induced changes in membrane ionic permeability induced by lytic viruses of many families contribute to cytopathogenesis. HIV-1 induces disturbances in plasma membrane ion transport. The carboxyl terminus of TM (gp41) contains potential amphipathic α-helical motifs identified through their structural similarities to naturally occurring cytolytic peptides. These sequences have been dubbed lentiviral lytic peptides (LLP) -1, -2, and -3.</p> <p>Results</p> <p>Peptides corresponding to the LLP domains (from a clade B virus) partition into lipid membranes, fold into α-helices and disrupt model membrane permeability. A peptide corresponding to the LLP-1 domain of a clade D HIV-1 virus, LLP-1D displayed similar activity to the LLP-1 domain of the clade B virus in all assays, despite a lack of amino acid sequence identity.</p> <p>Conclusion</p> <p>These results suggest that the C-terminal domains of HIV-1 Env proteins may form an ion channel, or viroporin. Increased understanding of the function of LLP domains and their role in the viral replication cycle could allow for the development of novel HIV drugs.</p

Neutralizing and non-neutralizing monoclonal antibodies against dengue virus E protein derived from a naturally infected patient

<p>Abstract</p> <p>Background</p> <p>Antibodies produced in response to infection with any of the four serotypes of dengue virus generally provide homotypic immunity. However, prior infection or circulating maternal antibodies can also mediate a non-protective antibody response that can enhance the course of disease in a subsequent heterotypic infection. Naturally occurring human monoclonal antibodies can help us understand the protective and pathogenic roles of the humoral immune system in dengue virus infection.</p> <p>Results</p> <p>Epstein-Barr Virus (EBV) transformation of B cells isolated from the peripheral blood of a human subject with previous dengue infection was performed. B cell cultures were screened by ELISA for antibodies to dengue (DENV) envelope (E) protein. ELISA positive cultures were cloned by limiting dilution. Three IgG1 human monoclonal antibodies (HMAbs) were purified and their binding specificity to E protein was verified by ELISA and biolayer interferometry. Neutralization and enhancement assays were conducted in epithelial and macrophage-like cell lines, respectively. All three HMAbs bound to E from at least two of the four DENV serotypes, one of the HMAbs was neutralizing, and all were able to enhance DENV infection.</p> <p>Conclusions</p> <p>HMAbs against DENV can be successfully generated by EBV transformation of B cells from patients at least two years after naturally acquired DENV infections. These antibodies show different patterns of cross-reactivity, neutralizing, and enhancement activity.</p

Structural Optimization and De Novo Design of Dengue Virus Entry Inhibitory Peptides

Viral fusogenic envelope proteins are important targets for the development of inhibitors of viral entry. We report an approach for the computational design of peptide inhibitors of the dengue 2 virus (DENV-2) envelope (E) protein using high-resolution structural data from a pre-entry dimeric form of the protein. By using predictive strategies together with computational optimization of binding “pseudoenergies”, we were able to design multiple peptide sequences that showed low micromolar viral entry inhibitory activity. The two most active peptides, DN57opt and 1OAN1, were designed to displace regions in the domain II hinge, and the first domain I/domain II beta sheet connection, respectively, and show fifty percent inhibitory concentrations of 8 and 7 µM respectively in a focus forming unit assay. The antiviral peptides were shown to interfere with virus:cell binding, interact directly with the E proteins and also cause changes to the viral surface using biolayer interferometry and cryo-electron microscopy, respectively. These peptides may be useful for characterization of intermediate states in the membrane fusion process, investigation of DENV receptor molecules, and as lead compounds for drug discovery

Beyond the Global Brain Differences:Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and globalbrain differences compared with noncarriers. However, interpreting regional differences is challenging if a globaldifference drives the regional brain differences. Intraindividual variability measures can be used to test for regionaldifferences beyond global differences in brain structure.METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n =30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matchednoncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual’sregional difference and global difference, were used to test for regional differences that diverge from the globaldifference.RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differedmore than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thicknessin regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal andsomatosensory cortex differed more than the global difference in cortical thickness.CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distaland 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distaland 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanismsinvolved in altered neurodevelopment

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genetic Testing to Inform Epilepsy Treatment Management From an International Study of Clinical Practice

IMPORTANCE: It is currently unknown how often and in which ways a genetic diagnosis given to a patient with epilepsy is associated with clinical management and outcomes. OBJECTIVE: To evaluate how genetic diagnoses in patients with epilepsy are associated with clinical management and outcomes. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective cross-sectional study of patients referred for multigene panel testing between March 18, 2016, and August 3, 2020, with outcomes reported between May and November 2020. The study setting included a commercial genetic testing laboratory and multicenter clinical practices. Patients with epilepsy, regardless of sociodemographic features, who received a pathogenic/likely pathogenic (P/LP) variant were included in the study. Case report forms were completed by all health care professionals. EXPOSURES: Genetic test results. MAIN OUTCOMES AND MEASURES: Clinical management changes after a genetic diagnosis (ie, 1 P/LP variant in autosomal dominant and X-linked diseases; 2 P/LP variants in autosomal recessive diseases) and subsequent patient outcomes as reported by health care professionals on case report forms. RESULTS: Among 418 patients, median (IQR) age at the time of testing was 4 (1-10) years, with an age range of 0 to 52 years, and 53.8% (n = 225) were female individuals. The mean (SD) time from a genetic test order to case report form completion was 595 (368) days (range, 27-1673 days). A genetic diagnosis was associated with changes in clinical management for 208 patients (49.8%) and usually (81.7% of the time) within 3 months of receiving the result. The most common clinical management changes were the addition of a new medication (78 [21.7%]), the initiation of medication (51 [14.2%]), the referral of a patient to a specialist (48 [13.4%]), vigilance for subclinical or extraneurological disease features (46 [12.8%]), and the cessation of a medication (42 [11.7%]). Among 167 patients with follow-up clinical information available (mean [SD] time, 584 [365] days), 125 (74.9%) reported positive outcomes, 108 (64.7%) reported reduction or elimination of seizures, 37 (22.2%) had decreases in the severity of other clinical signs, and 11 (6.6%) had reduced medication adverse effects. A few patients reported worsening of outcomes, including a decline in their condition (20 [12.0%]), increased seizure frequency (6 [3.6%]), and adverse medication effects (3 [1.8%]). No clinical management changes were reported for 178 patients (42.6%). CONCLUSIONS AND RELEVANCE: Results of this cross-sectional study suggest that genetic testing of individuals with epilepsy may be materially associated with clinical decision-making and improved patient outcomes

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice

Virology Journal BioMed Central Review Cytopathic Mechanisms of HIV-1

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Viroporin potential of the lentivirus lytic peptide (LLP) domains of the HIV-1 gp41 protein-5

<p><b>Copyright information:</b></p><p>Taken from "Viroporin potential of the lentivirus lytic peptide (LLP) domains of the HIV-1 gp41 protein"</p><p>http://www.virologyj.com/content/4/1/123</p><p>Virology Journal 2007;4():123-123.</p><p>Published online 20 Nov 2007</p><p>PMCID:PMC2211469.</p><p></p>ce of 90%POPC:10%POPG (filled squares). Spectroscopic analysis revealed that each peptide possessed the characteristic minima at 208 nm and 222 nm indicating α-helical character. (a) LLP-1 labeled with NBD; (b) LLP-2 labeled with NBD; (c) LLP-3; (d) LLP-1D labeled with NBD. (e) The percent α-helicity was calculated from the CD spectroscopy curves in figure a-d for each peptide using the following formula: Θ/(1–2.5/n)(40,000), where n = the number of residues present in the peptide