Biology subjects

Sreenivasan, S.

Publications and source records attributed to Sreenivasan, S..

7 recordsLinked to original sources

bioRxiv2026

RheoScale 2.0: Revealing the Hidden Roles of Protein Positions via Substitution Patterns

A central challenge in molecular biology is understanding how amino acid substitutions modulate various features of protein function and stability. To illuminate the complexities of this relationship, high-throughput (HTP) assays are increasingly used to assess site-saturating mutagenesis libraries. A common downstream analysis is to average the set of twenty outcomes at each amino acid position for comparison with structural and evolutionary features. Average values clearly identify positions that tolerate most substitutions (neutral positions) and positions where most substitutions abolish activity (toggle positions). However, average values conceal the existence of rheostat positions, where different amino acid substitutions sample a wide range of outcomes. To quantitatively identify rheostat positions, we previously developed a histogram-based analysis that we here expand by: (i) incorporating new position classes observed in experimental studies of rheostat positions; (ii) formalizing a hierarchy of class assignments; (iii) refining error-based identification of neutral positions; and (iv) statistically assessing the robustness of class assignments to changes in experimental and computational parameters. RheoScale 2.0 is implemented in Excel and newly implemented in Python for facile integration with existing HTP pipelines; all parameters are customizable. Example analyses are shown for three HTP datasets of the SARS-CoV-2 papain-like protease. Results illustrate two aspects that influence interpretation of HTP data: First, position assignments (and substitution outcomes) depend highly on the measured feature. Second, many protein positions play multiple roles in the sequence-structure-function relationship. The recognition of varied position roles will advance understanding of pathogen evolution, protein engineering, and variant interpretation for personalized medicine. SummaryRheoScale 2.0 improves how high-throughput mutational data are interpreted by identifying protein positions where amino acid substitutions act like biological dimmer switches. By enabling more nuanced assignment of position behavior, beyond neutral or deleterious outcomes, this analysis framework advances studies of sequence-structure-function relationships and has broad relevance for understanding protein evolution, engineering proteins with desired properties, and interpreting variants linked to human disease. SOFTWARE AVAILABILITYhttps://github.com/liskinsk/RheoScale-calculator

biochemistry↗

bioRxiv2026

Functional Profiling of Thousands of Sequence-Diverse Protease Homologs with GROQ-seq

High-quality datasets that span broad sequence diversity are essential for understanding protein sequence-function relationships beyond local mutational landscapes. Here, we applied Growth-based Quantitative Sequencing (GROQ-seq) to measure function across an 11,722 member protease library, comprised of natural homologs and AI-shrunken variants. This library spans vast sequence diversity, with Levenshtein distances of up to 245 and a mean pairwise sequence identity of 41% to TEV protease S219V. We identified sequence-divergent TEV protease homologs that preserve function against the native TEV protease substrate. These findings reveal the robustness of protease activity across highly diverse sequences. Here, we demonstrate the aptitude of the GROQ-seq assay for screening large, diverse protein libraries for function, enabling efficient data generation at scale for training machine learning models across broad sequence landscapes.

synthetic biology↗

bioRxiv2026

GROQ-seq Datasets Across Transcription Factors (LacI, RamR, VanR), T7 RNA Polymerase and TEV Protease

Predicting any proteins function from its sequence alone would be a significant breakthrough in molecular biology. Although machine learning approaches have sought to tackle this, their limited generalizability reflects the absence of sufficiently large, open, diverse, and unified datasets. To address this data gap, we developed a high-throughput experimental platform called GROQ-seq (Growth-based Quantitative Sequencing). In GROQ-seq, a proteins function can be linked to a sequencing-based readout that enables scalable characterization of large variant libraries in Escherichia coli. Here, we present pilot datasets demonstrating its performance across three distinct protein function classes: transcription factors, polymerases, and proteases. The objective of this report is to present the datasets and to provide users with a clear and transparent characterization of their properties, including both the strengths and limitations.

bioengineering↗

bioRxiv2025

Dissecting the effects of single amino acid substitutions in SARS-CoV2 Mpro

Successfully predicting the effects of amino acid substitutions on protein function and stability remains challenging. Recent efforts to improve computational models have included training and validation on high-throughput experimental datasets, such as those generated by deep mutational scanning (DMS) approaches. However, DMS signals typically conflate a substitutions effects on protein function with those on in vivo protein abundance; this limits the resolution of mechanistic insights that can be gleaned from DMS data. Distinguishing functional changes from abundance-related effects is particularly important for substitutions that exhibit intermediate outcomes (e.g., partial loss-of-function), which are difficult to predict. Here, we explored changes in in vivo abundance for substitutions at representative positions in the SARS-CoV-2 Main Protease (Mpro). For this study, we used previously published DMS results to identify "rheostat" positions, which are defined by having substitutions that sample a broad range of intermediate outcomes. We generated 10 substitutions at each of six positions and separately measured effects on function and abundance. Results revealed an [~]45-fold range of change for abundance, demonstrating that it can make significant contributions to DMS outcomes. Moreover, the six tested positions showed diverse substitution sensitivities for function and abundance. Some positions influenced only one parameter. Others exhibited rheostatic effects on both parameters, which to our knowledge, provides the first example of such behavior. Since effects on function and abundance may arise through different biophysical bases, these results underscore the need for datasets that independently measure these parameters in order to build predictors with enhanced mechanistic insights. ABSTRACT for broader audienceChanging one amino acid in a protein can affect its function, its abundance, or both. Understanding these separate effects will help scientists predict how protein changes alter biology, which is important for understanding pathogen evolution, improving personalized medicine, and bioengineering. This work reports a study to experimentally separate these effects for the main protease of SARS-CoV-2 and suggests strategies for building better prediction models for emerging variants of this key viral protein.

biochemistry↗

bioRxiv2023

Fructose-1-kinase has pleiotropic roles in Escherichia coli

In Escherichia coli, the master transcription regulator Catabolite Repressor Activator (Cra) regulates >100 genes in central metabolism. Cra binding to DNA is allosterically regulated by binding to fructose-1-phosphate (F-1-P), but the only documented source of F-1-P is from the concurrent import and phosphorylation of exogenous fructose. Thus, many have proposed that fructose-1,6-bisphosphate (F-1,6-BP) is also a physiological regulatory ligand. However, the role of F-1,6-BP has been widely debated. Here, we report that the E. coli enzyme fructose-1-kinase (FruK) can carry out its "reverse" reaction under physiological substrate concentrations to generate F-1-P from F-1,6-BP. We further show that FruK directly binds Cra with nanomolar affinity and forms higher order, heterocomplexes. Growth assays with a {Delta}fruK strain and fruK complementation show that FruK has a broader role in metabolism than fructose catabolism. The {Delta}fruK strain also alters biofilm formation. Since fruK itself is repressed by Cra, these newly-reported events add layers to the dynamic regulation of E. coli central metabolism that occur in response to changing nutrients. These findings might have wide-spread relevance to other {gamma}-proteobacteria, which conserve both Cra and FruK.

microbiology↗

bioRxiv2023

The intrinsically disordered transcriptional activation domain of CIITA is functionally tuneable by single substitutions: An exception or a new rule?

During protein evolution, some amino acid substitutions modulate protein function ("tuneability"). In most proteins, the tuneable range is wide and can be sampled by a set of protein variants that each contains multiple amino acid substitutions. In other proteins, the full tuneable range can be accessed by a set of variants that each contains a single substitution. Indeed, in some globular proteins, the full tuneable range can be accessed by the set of site-saturating substitutions at an individual "rheostat" position. However, in proteins with intrinsically disordered regions (IDRs), most functional studies - which would also detect tuneability - used multiple substitutions or small deletions. In disordered transcriptional activation domains (ADs), studies with multiple substitutions led to the "acidic exposure" model, which does not anticipate the existence of rheostat positions. In the few studies that did assess effects of single substitutions on AD function, results were mixed: The ADs of two full-length transcription factors did not show tuneability, whereas a fragment of a third AD was tuneable by single substitutions. Here, we tested tuneability in the AD of full-length human class II transactivator (CIITA). Sequence analyses and experiments showed that CIITAs AD is an IDR. Functional assays of singly-substituted AD variants showed that CIITAs function was highly tuneable, with outcomes not predicted by the acidic exposure model. Four tested positions showed rheostat behaviour for transcriptional activation. Thus, tuneability of different IDRs can vary widely. Future studies are needed to illuminate the biophysical features that govern whether an IDR is tuneable by single substitutions.

biochemistry↗

bioRxiv2022

Identification of a covert evolutionary pathway between two protein folds

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert -helices and {beta}-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcame these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We found that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus -helix+{beta}-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicated that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides methodology to identify secondary structure switching in other protein families.

bioinformatics↗