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1.
Infect Genet Evol ; 115: 105514, 2023 11.
Article in English | MEDLINE | ID: mdl-37832752

ABSTRACT

BACKGROUND: HIV subtype is associated with varied rates of disease progression. The HIV accessory protein, Nef, continues to be present during antiretroviral therapy (ART) where it has numerous immunoregulatory effects. In this study, we analyzed Nef sequences from HIV subtypes A1, B, C, and D using a machine learning approach that integrates functional amino acid information to identify if unique physicochemical features are associated with Nef functional/structural domains in a subtype-specific manner. METHODS: 2253 sequences representing subtypes A1, B, C, and D were aligned and domains with known functional properties were scored based on amino acid physicochemical properties. Following feature generation, we used statistical pruning and evolved neural networks (ENNs) to determine if we could successfully classify subtypes. Next, we used ENNs to identify the top five key Nef physicochemical features applied to specific immunoregulatory domains that differentiated subtypes. A signature pattern analysis was performed to the assess amino acid diversity in sub-domains that differentiated each subtype. RESULTS: In validation studies, ENNs successfully differentiated each subtype at A1 (87.2%), subtype B (89.5%), subtype C (91.7%), and subtype D (85.1%). Our feature-based domain scoring, followed by t-tests, and a similar ENN identified subtype-specific domain-associated features. Subtype A1 was associated with alterations in Nef CD4 binding domain; subtype B was associated with alterations with the AP-2 Binding domain; subtype C was associated with alterations in a structural Alpha Helix domain; and, subtype D was associated with alterations in a Beta-Sheet domain. CONCLUSIONS: Recent studies have focused on HIV Nef as a driver of immunoregulatory disease in those HIV infected and on ART. Nef acts through a complex mixture of interactions that are directly linked to the key features of the subtype-specific domains we identified with the ENN. The study supports the hypothesis that varied Nef subtypes contribute to subtype-specific disease progression.


Subject(s)
HIV Infections , HIV-1 , Humans , HIV-1/genetics , Amino Acid Sequence , nef Gene Products, Human Immunodeficiency Virus/genetics , Amino Acids/metabolism , Disease Progression
2.
F1000Res ; 10: 286, 2021.
Article in English | MEDLINE | ID: mdl-34113437

ABSTRACT

Background: Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes. Methods: We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level. Results: We show that the core regions determined by our method contain all or almost all essential genes. This demonstrates the accuracy of our method as essential genes should be core genes. We show that we outperform previous methods by this measure. We also explain why there are exceptions to this rule for our method. Conclusions: We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species.


Subject(s)
Bacillus subtilis , Escherichia coli , Bacillus subtilis/genetics , Computational Biology , Escherichia coli/genetics , Genome, Bacterial/genetics
3.
F1000Res ; 10: 354, 2021.
Article in English | MEDLINE | ID: mdl-35035886

ABSTRACT

Background: Wall teichoic acid (WTA) genes are essential for production of cell walls in gram-positive bacteria and necessary for survival and variability in the cassette has led to recent antibiotic resistance acquisition in pathogenic bacteria.  Methods: Using a pan-genome approach, we examined the evolutionary history of WTA genes in  Bacillus subtilis ssp.  subtilis.  Results: Our analysis reveals an interesting pattern of evolution from the type-strain WTA gene cassette possibly resulting from horizontal acquisition from organisms with similar gene sequences. The WTA cassettes have a high level of variation which may be due to one or more independent horizontal transfer events during the evolution of  Bacillus subtilis ssp.  subtilis. This swapping of entire WTA cassettes and smaller regions within the WTA cassettes is an unusual feature in the evolution of the  Bacillus subtilis genome and highlights the importance of horizontal transfer of gene cassettes through homologous recombination within  B. subtilis or other bacterial species.  Conclusions: Reduced sequence conservation of these WTA cassettes may indicate a modified function like the previously documented WTA ribitol/glycerol variation. An improved understanding of high-frequency recombination of gene cassettes has ramifications for synthetic biology and the use of  B. subtilis in industry.


Subject(s)
Bacillus subtilis , Bacterial Proteins , Bacillus subtilis/genetics , Cell Wall/genetics , Teichoic Acids
4.
J Neurovirol ; 24(1): 1-15, 2018 02.
Article in English | MEDLINE | ID: mdl-29063512

ABSTRACT

HIV-1 Nef is a flexible, multifunctional protein with several cellular targets that is required for pathogenicity of the virus. This protein maintains a high degree of genetic variation among intra- and inter-host isolates. HIV Nef is relevant to HIV-associated neurological diseases (HAND) in patients treated with combined antiretroviral therapy because of the protein's role in promoting survival and migration of infected brain macrophages. In this study, we analyzed 2020 HIV Nef sequences derived from 22 different tissues and 31 subjects using a novel computational approach. This approach combines statistical regression and evolved neural networks (ENNs) to classify brain sequences based on the physical and chemical characteristics of functional Nef domains. Based on training, testing, and validation data, the method successfully classified brain Nef sequences at 84.5% and provided informative features for further examination. These included physicochemical features associated with the Src-homology-3 binding domain, the Nef loop (including the AP-2 Binding region), and a cytokine-binding domain. Non-brain sequences from patients with HIV-associated neurological disease were frequently classified as brain, suggesting that the approach could indicate neurological risk using blood-derived virus or for the development of biomarkers for use in assay systems aimed at drug efficacy studies for the treatment of HIV-associated neurological diseases.


Subject(s)
AIDS Dementia Complex/virology , Brain/virology , HIV-1/genetics , Host-Pathogen Interactions/genetics , nef Gene Products, Human Immunodeficiency Virus/chemistry , AIDS Dementia Complex/drug therapy , AIDS Dementia Complex/genetics , AIDS Dementia Complex/physiopathology , Amino Acid Sequence , Anti-HIV Agents/therapeutic use , Antiretroviral Therapy, Highly Active , Autopsy , Binding Sites , Brain/metabolism , Brain/pathology , Gene Expression , HIV-1/metabolism , HIV-1/pathogenicity , Humans , Lymphoid Tissue/metabolism , Lymphoid Tissue/pathology , Lymphoid Tissue/virology , Macrophages/metabolism , Macrophages/pathology , Macrophages/virology , Models, Molecular , Neural Networks, Computer , Organ Specificity , Protein Binding , Protein Conformation, alpha-Helical , Protein Conformation, beta-Strand , Protein Interaction Domains and Motifs , Sequence Alignment , Sequence Homology, Amino Acid , Signal Transduction , nef Gene Products, Human Immunodeficiency Virus/genetics , nef Gene Products, Human Immunodeficiency Virus/metabolism
5.
AIDS Res Hum Retroviruses ; 32(8): 829-40, 2016 08.
Article in English | MEDLINE | ID: mdl-27071630

ABSTRACT

HIV-1 enters immune cells via binding the viral envelope to a host cell CD4 receptor, and then a secondary co-receptor, usually CCR5 (R5) or CXCR4 (X4), and some HIV can utilize both co-receptors (R5X4). Although a small set of amino-acid properties such as charge and sequence length applied to HIV-1 envelope V3 loop sequence data can be used to predict co-receptor usage, we sought to expand the fundamental understanding of the physiochemical basis of tropism by analyzing many, perhaps less obvious, amino-acid properties over a diverse array of HIV sequences. We examined 74 amino-acid physicochemical scales over 1,559 V3 loop sequences with biologically tested tropisms downloaded from the Los Alamos HIV sequence database. Linear regressions were then calculated for each feature relative to three tropism transitions (R5→X4; R5→R5X4; R5X4→X4). Independent correlations were rank ordered to determine informative features. A structural analysis of the V3 loop was performed to better interpret these findings relative to HIV tropism states. Similar structural changes are required for R5 and R5X4 to transition to X4, thus suggesting that R5 and R5X4 types are more similar than either phenotype is to X4. Overall, the analysis suggests a continuum of viral tropism that is only partially related to charge; in fact, the analysis suggests that charge modification may be primarily attributed to decreased R5 usage, and further structural changes, particularly those associated with ß-sheet structure, are likely required for full X4 usage.


Subject(s)
CD4 Antigens/metabolism , HIV Envelope Protein gp120/metabolism , HIV-1/metabolism , Receptors, CCR5/metabolism , Receptors, CXCR4/metabolism , T-Lymphocytes/virology , Viral Tropism/genetics , Amino Acid Sequence , Binding Sites , CD4 Antigens/chemistry , CD4 Antigens/genetics , Databases, Genetic , HIV Envelope Protein gp120/chemistry , HIV Envelope Protein gp120/genetics , HIV-1/classification , HIV-1/genetics , Humans , Hydrophobic and Hydrophilic Interactions , Molecular Dynamics Simulation , Phenotype , Protein Binding , Protein Conformation, alpha-Helical , Protein Conformation, beta-Strand , Protein Interaction Domains and Motifs , Receptors, CCR5/chemistry , Receptors, CCR5/genetics , Receptors, CXCR4/chemistry , Receptors, CXCR4/genetics , Sequence Alignment , Sequence Homology, Amino Acid , Static Electricity , Thermodynamics , Virus Attachment
6.
Biosystems ; 137: 12-9, 2015 Nov.
Article in English | MEDLINE | ID: mdl-26419858

ABSTRACT

Blocking the binding of the envelope HIV-1 protein to immune cells is a popular concept for development of anti-HIV therapeutics. R5 HIV-1 binds CCR5, X4 HIV-1 binds CXCR4, and dual-tropic HIV-1 can bind either coreceptor for cellular entry. R5 viruses are associated with early infection and over time can evolve to X4 viruses that are associated with immune failure. Dual-tropic HIV-1 is less studied; however, it represents functional antigenic intermediates during the transition of R5 to X4 viruses. Viral tropism is linked partly to the HIV-1 envelope V3 domain, where the amino acid sequence helps dictate the receptor a particular virus will target; however, using V3 sequence information to identify dual-tropic HIV-1 isolates has remained difficult. Our goal in this study was to elucidate features of dual-tropic HIV-1 isolates that assist in the biological understanding of dual-tropism and develop an approach for their detection. Over 1559 HIV-1 subtype B sequences with known tropisms were analyzed. Each sequence was represented by 73 structural, biochemical and regional features. These features were provided to an evolved neural network classifier and evaluated using balanced and unbalanced data sets. The study resolved R5X4 viruses from R5 with an accuracy of 81.8% and from X4 with an accuracy of 78.8%. The approach also identified a set of V3 features (hydrophobicity, structural and polarity) that are associated with tropism transitions. The ability to distinguish R5X4 isolates will improve computational tropism decisions for R5 vs. X4 and assist in HIV-1 research and drug development efforts.


Subject(s)
HIV-1/physiology , Neural Networks, Computer , Viral Tropism , Models, Theoretical
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