Search bioRxiv⌕ Search

Biology subjects

Khasanova, A.

Publications and source records attributed to Khasanova, A..

3 recordsLinked to original sources

Expanding the HIF-2α proteomic interactome with TurboID proximity labeling.

The transcription factor HIF2 is a central regulator of cellular adaptation to hypoxia, orchestrating gene expression programs that control angiogenesis, erythropoiesis, and metabolic reprogramming, and is famously overexpressed in cancers such as clear cell Renal Cell Carcinoma (ccRCC). While the gene targets of HIF2 have been extensively characterized, the composition and dynamics of its protein interaction network remain less well defined. In this study, we sought to systematically characterize proteins associated with HIF2 using two distinct proteomic approaches, enabling the identification of both stable binding partners and transient or indirect interactors. We integrated affinity purification mass spectrometry with proximity labeling strategies, thus expanding the existing interactome of HIF2 to include uniquely identified proteins and complexes such as members of the nuclear pore complex. Across both immunoprecipitation mass spectrometry (IP MS) and TurboID MS, we identified 888 and 1,048 proteins, respectively. We applied stringent filtering criteria to refine both datatsets, yielding a dataset of 329 HIF2 interacting proteins, approximately 75% of which have yet to be documented as HIF2 interactors. We queried this set across publicly available cancer genomics and proteomics datasets and detected expression of our interactors in breast cancer and ccRCC tumor proteomes. These findings led us to identify GRHL2 and KIF4A as proteomic interactors that contribute to poor patient survival in breast cancer. Taken together, we herein provide a comprehensive resource of HIF2 interacting proteins which provide insights into the mechanisms by which HIF2 drives disease progression.

biochemistry↗

Breeding of microbiomes conferring salt tolerance to plants

Microbiome breeding by host-mediated selection is a technique to artificially select for microbiomes conferring benefits to plants. Here, we describe leaf ionomics, microbial community composition, and network analyses of a microbiome-breeding experiment to generate microbiomes conferring salt tolerance to Brachypodium distachyon, a model for cereal crops. Plants receiving microbiomes selected to confer tolerance to either sodium- or aluminium-stress produced 69-198% higher total seed weight than plants receiving control microbiomes. Sodium-selected microbiomes reduced leaf-sodium concentration by 50%, whereas aluminium-selected microbiomes had no effect on leaf-tissue nutrient concentration, suggesting different mechanisms underlying microbiome-mediated salt tolerance. By testing these selected microbiomes in a cross-fostering experiment, we show that artificially-selected microbiomes attain (a) ecological robustness contributing to transplantability (inheritance) of microbiome-encoded effects between plants; and (b) network features identifying key bacteria promoting stress tolerance. Combined, these findings elucidate critical mechanisms underlying host-mediated selection as a tool to breed beneficial microbiomes in an agricultural context.

evolutionary biology↗

The genetic architecture of shoot and root trait divergence between upland and lowland ecotypes of a perennial grass.

Introduction Introduction Materials and Methods Results Discussion Conclusion Author Contributions: References Adaptation to abiotic stress is an important driver of contemporary evolution in plant populations. Abiotic stressors have been implicated as driving factors in ecological speciation (Stebbins, 1952;Lexer & Fay, 2005), where populations have diverged across a number of traits, exhibit different niche characteristics, and eventually become reproductively isolated (Clausen, 1951; Lowry, 2012; Yardeni et al., 2016). Local adaptation to soil water availability is an especially important driver of plant evolution (Stebbins, 1952; Rajakaruna, 2004; ...

plant biology↗