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Biomedical subjects

Ivan Ivanov

Publications and source records attributed to Ivan Ivanov.

14 recordsLinked to original sources
PubMed2026

Inclusion of Multi-Omic Biomarkers Improves Prediction Accuracy of Response, Relapse, and Overall Survival in Acute Myeloid Leukemia Patients Receiving High-Intensity Induction Chemotherapy.

BACKGROUND: Despite advancements in genetic markers for acute myeloid leukemia (AML) risk stratification, outcome prediction remains challenging due to disease heterogeneity and dynamic genetic changes, highlighting the need for reliable biomarkers to improve AML treatment strategies and patient outcomes. To refine outcome predictions, we investigated the use of microbial-derived biomarkers to predict composite complete remission (CRc), relapse, and survival for patients on high- and low-intensity regimens, and to integrate those variables into the widely clinically utilized European Leukemia Network (ELN-2022) genetic risk classification model for high-intensity-treated patients. METHODS: We first developed machine learning models that integrate baseline fecal metabolomics, 16S rRNA-based stool microbiome features, and clinical metadata (sex, antibiotic administration, AML somatic mutations, and cytogenetics) from two cohorts of AML patients (n = 83) undergoing remission induction chemotherapy. Univariate tests and sparse canonical correlation analysis were employed for variable selection and to explore fecal metabolite-microbe relationships. A robust machine learning approach using XGBoost was employed, with 100 stratified data splits (80% training, 20% testing) and coarse-to-fine hyperparameter optimization. Variable importance was aggregated across all models to select key predictors. RESULTS: For high-intensity-treated patients, XGBoost models achieved aggregated AUROC scores of 0.719, 0.729, and 0.65 for CRc, relapse, and overall survival, respectively. For low-intensity-treated patients, these models achieved aggregate AUROC scores of 0.945, 0.724, and 0.768 for these same outcomes, respectively. Integrating the biomarkers identified in the high-intensity machine-learning models with the current ELN-2022 AML risk stratification system effectively stratified patients into risk categories, which obtained higher concordance indices and likelihood ratios, demonstrating improved prognostic accuracy for each outcome compared to ELN-2022 alone. CONCLUSIONS: The inclusion of microbial-derived biomarkers serves as a robust prognostic tool to improve outcome prediction in AML patients, highlighting the potential of its integration into AML risk assessment and paving the way for personalized treatment strategies and improved patient outcomes.

Humans↗
PubMed2007

Investigating the in vivo activity of the DeaD protein using protein-protein interactions and the translational activity of structured chloramphenicol acetyltransferase mRNAs.

Here, we report the use of an in vivo protein-protein interaction detection approach together with focused follow-up experiments to study the function of the DeaD protein in Escherichia coli. In this method, functions are assigned to proteins based on the interactions they make with others in the living cell. The assigned functions are further confirmed using follow-up experiments. The DeaD protein has been characterized in vitro as a putative prokaryotic factor required for the formation of translation initiation complexes on structured mRNAs. Although the RNA helicase activity of DeaD has been demonstrated in vitro, its in vivo activity remains controversial. Here, using a method called sequential peptide affinity (SPA) tagging, we show that DeaD interacts with certain ribosomal proteins as well as a series of other nucleic acid binding proteins. Focused follow-up experiments provide evidence for the mRNA helicase activity of the DeaD protein complex during translation initiation. DeaD overexpression compensates for the reduction of the translation activity caused by a structure placed at the initiation region of a chloramphenicol acetyltransferase gene (cat) used as a reporter. Deletion of the deaD gene, encoding DeaD, abolishes the translation activity of the mRNA with an inhibitory structure at its initiation region. Increasing the growth temperature disrupts RNA secondary structures and bypasses the DeaD requirement. These observations suggest that DeaD is involved in destabilizing mRNA structures during translation initiation. This study also provides further confirmation that large-scale protein-protein interaction data can be suitable to study protein functions in E. coli.

Base Sequence↗
PubMed2006

Tularemia outbreak, Bulgaria, 1997-2005.

The 1997-2005 tularemia outbreak in Bulgaria affected 285 people. Ten strains were isolated from humans, a tick, a hare, and water. Amplified fragment length polymorphism typing of the present isolates and of the strain isolated in 1962 suggests that a new genetic variant caused the outbreak.

Animals↗
PubMed2006

Plasma lipids and blood viscosity in patients with cerebrovascular disease.

It is known that plasma lipids could increase the cerebrovascular risk through alteration of the hemorheological profile. The aim of the study was to evaluate the relationship between blood viscosity parameters and plasma lipids in patients with cerebrovascular disease (CVD). The study included 43 patients with transient ischemic attacks (TIAs), 53 patients with chronic unilateral cerebral infarctions (UCI) and 57 patients with risk factors (RF) for CVD. Whole blood viscosity (WBV) at different shear rates by Couette rotational viscometer Contraves Low Shear 30, plasma viscosity (PV) with capillary viscometer, hematocrit (Hct), fibrinogen (Fib), Cholesterol (Chol), triglycerides (Tg) and high-density lipoproteins (HDL) were examined in all patients and in a control group of 56 presumed healthy subjects. The hemorheological results showed increase of Hct, Fib, WBV and PV in the patients with TIAs and UCI; it was more pronounced in the UCI patients. Significant increase of Hct and WBV in the group with RF for CVD was also found. The elevation of Chol and Tg predominated in the patients with UCI and in the subjects with RF for CVD. These lipid variables correlated significantly with PV in the TIAs and RF for CVD groups. Conclusion is drawn about the significance of plasma Tg for decrease of blood fluidity and for impairment of the cerebral circulation in CVD.

Aged↗
PubMed2006

Hemorheological parameters in correlation with the risk factors for carotid atherosclerosis.

The study aimed to follow the relationship between some hemorheological variables and the main risk factors (RF) for carotid atherosclerosis (CA). Carotid atherosclerosis was evaluated by color duplex sonography of the carotid arteries in 18 patients with RF for CA, 31 patients with transient ischemic attacks (TIAs), 21 patients with chronic unilateral cerebral infarctions (UCI) and 11 healthy subjects without RF for CA. The examined hemorheological variables were whole blood and plasma viscosity, hematocrit and fibrinogen. They were correlated with intima-media thickness (IMT) of the common carotid and the internal carotid arteries and with other main RF for CA: hypertension, diabetes mellitus, coronary heart disease, and hyperlipidemia. The hemorheological investigation showed an increase in blood and plasma viscosity at different shear rates and it was more expressed in the group with UCI. The neurosonographic investigation revealed an increase in the IMT and carotid artery stenoses in the patients' groups with CVD. These were also more frequent in the patients with UCI. Different correlations were established between the hemorheological parameters, the IMT of the carotid arteries and other RF for CA. In the group with UCI, the hematocrit and the whole blood viscosity correlated significantly with the IMT, arterial blood pressure and cholesterol values. These data confirm the influence of the hemorheological parameters on carotid blood vessel walls and on blood flow in patients with CVD.

Atherosclerosis↗
PubMed2005

Generating Boolean networks with a prescribed attractor structure.

MOTIVATION: Dynamical modeling of gene regulation via network models constitutes a key problem for genomics. The long-run characteristics of a dynamical system are critical and their determination is a primary aspect of system analysis. In the other direction, system synthesis involves constructing a network possessing a given set of properties. This constitutes the inverse problem. Generally, the inverse problem is ill-posed, meaning there will be many networks, or perhaps none, possessing the desired properties. Relative to long-run behavior, we may wish to construct networks possessing a desirable steady-state distribution. This paper addresses the long-run inverse problem pertaining to Boolean networks (BNs). RESULTS: The long-run behavior of a BN is characterized by its attractors. The rest of the state transition diagram is partitioned into level sets, the j-th level set being composed of all states that transition to one of the attractor states in exactly j transitions. We present two algorithms for the attractor inverse problem. The attractors are specified, and the sizes of the predictor sets and the number of levels are constrained. Algorithm complexity and performance are analyzed. The algorithmic solutions have immediate application. Under the assumption that sampling is from the steady state, a basic criterion for checking the validity of a designed network is that there should be concordance between the attractor states of the model and the data states. This criterion can be used to test a design algorithm: randomly select a set of states to be used as data states; generate a BN possessing the selected states as attractors, perhaps with some added requirements such as constraints on the number of predictors and the level structure; apply the design algorithm; and check the concordance between the attractor states of the designed network and the data states. AVAILABILITY: The software and supplementary material is available at http://gsp.tamu.edu/Publications/BNs/bn.htm

Algorithms↗
PubMed2005

Evidence for non-enzymatic glycosylation of Escherichia coli chromosomal DNA.

We have recently shown that the process of non-enzymatic glycosylation (glycation) takes place in Escherichia coli under physiological conditions and affects both recombinant and endogenous bacterial proteins. In this study, we further demonstrate that E. coli chromosomal DNA is also subjected to glycation under physiological growth conditions. The E. coli DNA accumulates early glycation (Amadori) products as proven by the nitroblue tetrazolium (NBT) reduction assay. It showed also immunoreactivity to a monoclonal antibody raised against N(in)-(carboxymethyl)lysine and fluorescent properties indicative of modifications with advanced glycation end-products. Two types of fluorophores were detected in the E. coli DNA with excitation maxima at 360 nm and 380 nm and emission maxima at 440 nm and 410 nm. Using the NBT reduction assay, fluorescence spectroscopy and enzyme-linked immunosorbent assay we revealed that glycation adducts accumulate in DNA predominantly in the stationary phase of growth, although they could be detected also in exponential-phase cells. Besides on the growth phase, the extent of DNA glycation depends also on the nutrient broth composition being more extensive in rich media. Thiamine was found to inhibit both DNA glycation and spontaneous point mutations as judged by the decreased rate of the argE3 to Arg(+) reversions in the E. coli strain AB1157.

Chromosomes, Bacterial↗
PubMed2004

A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks.

MOTIVATION: We have hypothesized that the construction of transcriptional regulatory networks using a method that optimizes connectivity would lead to regulation consistent with biological expectations. A key expectation is that the hypothetical networks should produce a few, very strong attractors, highly similar to the original observations, mimicking biological state stability and determinism. Another central expectation is that, since it is expected that the biological control is distributed and mutually reinforcing, interpretation of the observations should lead to a very small number of connection schemes. RESULTS: We propose a fully Bayesian approach to constructing probabilistic gene regulatory networks (PGRNs) that emphasizes network topology. The method computes the possible parent sets of each gene, the corresponding predictors and the associated probabilities based on a nonlinear perceptron model, using a reversible jump Markov chain Monte Carlo (MCMC) technique, and an MCMC method is employed to search the network configurations to find those with the highest Bayesian scores to construct the PGRN. The Bayesian method has been used to construct a PGRN based on the observed behavior of a set of genes whose expression patterns vary across a set of melanoma samples exhibiting two very different phenotypes with respect to cell motility and invasiveness. Key biological features have been faithfully reflected in the model. Its steady-state distribution contains attractors that are either identical or very similar to the states observed in the data, and many of the attractors are singletons, which mimics the biological propensity to stably occupy a given state. Most interestingly, the connectivity rules for the most optimal generated networks constituting the PGRN are remarkably similar, as would be expected for a network operating on a distributed basis, with strong interactions between the components.

Algorithms↗
PubMed2003

Glycation and post-translational processing of human interferon-gamma expressed in Escherichia coli.

Until recently, nonenzymatic glycosylation (glycation) was thought to affect the proteins of long living eukaryotes only. However, in a recent study (Mironova, R., Niwa, T., Hayashi, H., Dimitrova, R., and Ivanov, I. (2001) Mol. Microbiol. 39, 1061-1068), we have shown that glycation takes place in Escherichia coli as well. In the present study, we demonstrate that the post-translational processing (proteolysis and covalent dimerization) observed with cysteineless recombinant human interferon-gamma (rhIFN-gamma) is tightly associated with its in vivo glycation. Our results show that, at the time of isolation, rhIFN-gamma contained early (but not advanced) glycation products. Using reverse phase high performance liquid chromatography in conjunction with fluorescence measurements, enzyme-linked immunosorbent assay, and mass spectrometry, we found that advanced glycation end products arose in rhIFN-gamma during storage. The latter were identified mainly in the Arg/Lys-rich C terminus of the protein, which was also the main target of proteolysis. Mass spectral analysis and N-terminal sequencing revealed four major (Arg140/Arg141, Phe137/Arg138, Met135/Leu136, and Lys131/Arg132) and two minor (Lys109/Ala110 and Arg90/Asp91) cleavage sites in this region. Tryptic peptide mapping indicated that the covalent dimers of rhIFN-gamma originating during storage were formed mainly by lateral cross-linking of the monomer subunits. Antiviral assay showed that proteolysis lowered the antiviral activity of rhIFN-gamma, whereas covalent dimerization completely abolished it.

Amino Acid Sequence↗
PubMed2003

Molecular cloning, expression and characterization of three distinctive genes encoding methionine aminopeptidases in cyanobacterium Synechocystis sp. strain PCC6803.

Methionine aminopeptidase, known to be encoded by single genes in prokaryotes, is a cobalt-dependent enzyme that catalyzes the removal of N-terminal methionine residues from nascent polypeptides. Three ORFs encoding putative methionine aminopeptidases from the genome of cyanobacterium Synechocystis sp. strain PCC6803, designated as slr0786 ( map-1), slr0918 ( map-2) and sll0555 ( map-3) were cloned and expressed in Escherichia coli. The purified recombinant proteins encoded by map-1 and map-3 had much higher methionine aminopeptidase activity than the recombinant protein encoded by map-2. Comparative analysis revealed that the three recombinant enzymes differed in their substrate specificity, divalent ion requirement, pH, and temperature optima. The broad activities of the iso-enzymes are discussed in light of the structural similarities with other peptidase families and their levels of specificity in the cell. Potential application of cyanobacterial MetAPs in the production of recombinant proteins used in medicine is proposed. This is the first report of a prokaryote harboring multiple methionine aminopeptidases.

Amino Acid Sequence↗
PubMed2003

Codon pairs in the genome of Escherichia coli.

MOTIVATION: The effect of two neighboring codons (codon pairs) on gene expression is mediated via the interaction of their cognate tRNAs occupying the two functional ribosomal sites during the translation elongation step. For steric reasons it is reasonable to assume that not all combinations of codons and therefore of tRNAs are equally favorable when situated on the ribosome surface. Aiming of identifying preferential and rare codon pairs, we have determined the frequency of occurrence of all possible combinations of codon pairs in the entire genome of Escherichia coli (E.coli). RESULTS: The frequency of occurrence of the 3904 codon pairs comprising both sense:sense and sense:stop codon pairs in the full set of E.coli 4289 ORFs was found to vary from zero to 4913 times. For most of the pairs we have observed a significant difference between the real and statistically predicted frequency of occurrence. The analysis of 334 highly expressed and 303 poorly expressed E.coli genes showed that codon pair usage is different for the two gene categories. Using an especially defined criterion (Delta(REG)), the codon pairs are classified as 'hypothetically attenuating' (HAP) and 'hypothetically non-attenuating' (HNAP) and their possible effect on translation is discussed. AVAILABILITY: The program used in this study is available at http://www.bio21.bas.bg/codonpairs/

Algorithms↗
PubMed2003

Human interferon gamma: significance of the C-terminal flexible domain for its biological activity.

The significance of the C-terminal part of human interferon gamma (hIFNgamma) for its biological activity was studied by 3(')-end gene mutagenesis. A series of nine derivative genes obtained by systemic deletion of three codons was constructed and expressed in Escherichia coli LE392. It was shown that the yield of recombinant protein gradually decreased and the solubility gradually increased with truncation of the C terminus. To avoid artifacts related to the imperfect folding of the proteins during purification, the biological activity of the hIFNgamma proteins was measured in clear cell lysates containing the soluble fractions only. The deletion of the C terminus had a two-step effect on both hIFNgamma antiviral and antiproliferative activities. Whereas the removal of the last 3, 6, and 9 C-terminal amino acids led to a gradual increase (up to 10 times) in biological activity of hIFNgamma, the deletion of more than 9 amino acids had an opposite effect. The truncation of the whole unstructured C-terminal domain resulted in a 10-fold decrease (but not in a complete loss) in biological activity of hIFNgamma. The latter was sequestered upon deletion of 24 amino acids, 3 of which belonged to the alpha-helical domain F.

Amino Acid Sequence↗