Biology subjects

Mihnev, A.

Publications and source records attributed to Mihnev, A..

3 recordsLinked to original sources

bioRxiv2026

Stochasticity in Metabolism: Oxidative Stress Response Phenotypes As Emergent Consequences of Network Topology

Reactive oxygen species (ROS) are ubiquitous yet elusive due to their reactivity and short half-lives, making simulation essential for mechanistic insight. Traditional ROS modeling has been confined to small ODE frameworks limited by kinetic-parameter scarcity. Here, we recast ROS dynamics as a flux-balance analysis (FBA) optimization problem using COBRA and CPLEX, augmenting the Escherichia coli iJO1366 genome-scale model with 84 spontaneous oxidation, 14 redox, and 9 detoxification reactions, targeting three ROS species: hydroxyl radicals, superoxide, and hydrogen peroxide (H2O2). We also formalize five fundamental rules of oxidation biology in the form of mixed-integer linear constraints, allowing us to dynamically incorporate reaction rate constants and let complex behavior emerge from first principles. Among these phenomena is the bimodal killing pattern under H2O2 stress, first announced over 40 years ago and never computationally recapitulated until now. We observe it by stochastically sampling our models with GapSplit, simulating bet-hedging and partitioning solutions into growers, persisters, and non-survivors. In our simulations, this killing effect arises solely from the metabolic network topology during random exploration of alternative metabolic configurations. The conservation of steady state creates a stochastic bias for detoxification when central carbon metabolism reaches its metabolic capacity to deal with ROS, causing the famous survival recovery phase. The recovery phase is thus part of Mode 1 metabolism, characterized by spare detoxification capacity and fulfilled by the Ahp reaction in E. coli. Mode 2 has no spare detoxification. We anticipate this to be an overlooked universal principle.

systems biology↗

bioRxiv2022

In-silico analysis of cyanobacteriochrome architectures and spectral diversity

The cyanobacteriochrome GAF domains represent a trove of spectral diversity. These proteins are endemic to cyanobacteria and sense the color and power of light. Multiple mechanisms are used to tune the natural absorbance spectrum of the bound bilin chromophore. In practice, these are difficult to identify from the predicted amino acid sequence. Their individual presence rarely yields a consistent and predictable outcome. The absorbance characteristics of the GAF domain are a complex function of many such tuning mechanisms. This implies that a more combinatoric approach to characterizing the diversity of GAF domains would better to predict spectral tunes. We reviewed the literature and constructed a dataset of predicted/confirmed cyanobacteriochrome GAF domains. This dataset was subjected to multiple sequence alignments and 18 GAF domain families were defined. The amino acid sequence similarity correlated well with known spectral characteristics but there were exceptions. A second approach to predict chromotype involved using Principal Component Analysis to characterize the whole domain architectures of cyanobacteriochrome. This approach identified 7 conserved domain architectures, with some variations. These also offered a correlation to the spectral tune of the GAF domains therein, in addition to the 18 GAF families. The three-dimensional structures of 98 spectrally characterized GAF domains were predicted using Phyre2. Subsequent grouping based on distance maps offered an insight into how the general spectral position of the domain is set. Finer tuning is likely to be achieved by means of six key residues within the binding pocket. Taken together, these insights allowed us to carry out a Multiple Correlation Analysis serving as a mathematical summary of the diversity of cyanobacteriochrome GAF domains. This summary or "cyanobacteriochrome atlas" can be used to make spectral predictions on uncharacterized GAF domains.

biochemistry↗

bioRxiv2022

Photocycle characterization of a blue-orange cyanobacteriochrome from Synechococcus sp. PCC 7002

Cyanobacteria employ photoreceptors called cyanobacteriochromes (CBCRs) to sense the colour and intensity of light. The information extracted from the solar spectrum is used for adaptive responses such as optimizing photosynthesis, phototaxis and cell aggregation. cGMP-phosphodiesterase/adenlylate cyclase/FhlA (GAF) domains are the principal light sensors in cyanobacteriochromes. They contain a conjugated bilin chromophore and boast an impressive spectral diversity. Characterizing the spectral characteristics of GAF domains in model strains, such as Synechococcus sp. PCC 7002, can open new avenues for optogenetics and biotechnology. Based on sequence analysis we predicted several different GAF domains in this strain. The SynPCC7002_a0852 gene encodes a single GAF domain with two cysteine residues: one in the conserved 3 helix and one in the conserved DXCF motif. Spectral analysis of recombinant SynPCC7002_A0852 with phycocyanobilin (PCB) showed that the protein cycles between two states, Po and Pb, which absorb orange and blue light, respectively. Measurements of kinetics identified Po as the dark state of the protein. Acid-denaturation analysis suggested that the 15E isomer of PCB is bound in the (dark) Po state, whereas 15Z is bound the (photoproduct) Pb state. Site-directed mutagenesis and iodoacetamide treatments showed that Cys73 in the DXCF motif is essential for the conversion from Po to Pb. Future experiments dark-purified protein/chromophore versions are required to establish the sequence of events in the photocycle. In summary, SynPCC7002_A0852 enables orange/blue colour perception in Synechococcus sp. PCC 7002 as other CBRCs of this protein family but might contain the energetically higher chromophore isoform in its dark state. Such photocycle has previously been found in bathy bacteriophytochromes but not in CBCRs.

molecular biology↗