Biology subjects

Basu, S.

Publications and source records attributed to Basu, S..

At least 145 records · Page 8Linked to original sources

bioRxiv2022

BML-257, a small molecule that protects against drug induced liver injury in zebrafish

The use of many essential drugs is restricted due to their deleterious effects on the liver. Molecules that can prevent or protect the liver from drug induced liver injury (DILI) would be valuable in such situations. We used hepatocyte-specific expression of bacterial nitroreductase in zebrafish to cause temporally controlled liver damage. This transgenic line was used to run a whole organism based chemical screen in zebrafish larvae. In this screen we identified BML-257, a potent small molecule AKT inhibitor, that protected the liver against metronidazole-induced liver injury. BML-257 also showed potent prophylactic and pro-regenerative activity in this liver damage model. BML-257 also showed remarkable protective action in two independent toxicological models of liver injury caused by acetaminophen and Isoniazid. This suggests that BML-257 may have the potential to protect against multiple kinds of drug induced liver injury.

molecular biology↗

bioRxiv2021

Capturing a crucial 'disorder-to-order transition' at the heart of the coronavirus molecular pathology - triggered by highly persistent, interchangeable salt-bridges

The COVID-19 origin debate has greatly been influenced by Genome comparison studies of late, revealing the seemingly sudden emergence of the Furin-Like Cleavage Site at the S1/S2 junction of the SARS-CoV-2 Spike (FLCSSpike) containing its 681PRRAR685 motif, absent in other related respiratory viruses. Being the rate-limiting (i.e., the slowest) step, the host Furin cleavage is instrumental in the abrupt increase in transmissibility in COVID-19, compared to earlier onsets of respiratory viral diseases. In such a context, the current paper entraps a disorder-to-order transition of the FLCSSpike (concomitant to an entropy arrest) upon binding to Furin. The interaction clearly seems to be optimized for a more efficient proteolytic cleavage in SARS-CoV-2. The study further shows the formation of dynamically interchangeable and persistent networks of salt-bridges at the Spike-Furin interface in SARS-CoV-2 involving the three arginines (R682, R683, R685) of the FLCSSpike with several anionic residues (E230, E236, D259, D264, D306) coming from Furin, strategically distributed around its catalytic triad. Multiplicity and structural degeneracy of plausible salt-bridge network archetypes seems the other key characteristic features of the Spike-Furin binding in SARS-CoV-2 allowing the system to breathe - a trademark of protein disorder transitions. Interestingly, with respect to the homologous interaction in SARS-CoV (2002/2003) taken as a baseline, the Spike-Furin binding events generally in the coronavirus lineage seems to have a preference for ionic bond formation, even with lesser number of cationic residues at their potentially polybasic FLCSSpike patches. The interaction energies are suggestive of a characteristic metastabilities attributed to Spike-Furin interactions generally to the coronavirus lineage - which appears to be favorable for proteolytic cleavages targeted at flexible protein loops. T he current findings not only offer novel mechanistic insights into the coronavirus molecular pathology and evolution but also add substantially to the existing theories of proteolytic cleavages.

biophysics↗

bioRxiv2021

Two Liberibacter Effectors Combine to Suppress Critical Innate Immune Defenses and Facilitate Huanglongbing Pathogenesis in Citrus

Genome sequence analyses predicted the presence of effectors in the gram-negative Candidatus Liberibacter asiaticus (CLas) even without the presence of a classical type III secretion system. Since CLas is not culturable, it is not possible to perform traditional gene knockout experiments to determine the role of various effectors in Huanglongbing (HLB) pathogenesis. Therefore, we followed an alternative functional genomics approach to examine the role of the CLas effectors in HLB pathogenesis in general and more specifically in suppressing citrus innate immune response. Here, we focused on the CLas effectors, P235 and Effector 3, to perform the following studies. First, proteomic studies by LC-MS/MS were conducted to screen the putative interacting citrus protein partners of P235 and Effector 3 from the healthy and CLas-infected Hamlin extracts and the most probable candidates were identified based upon their high protein scores from LC-MS/MS. Second, a transgenic tobacco split GFP system was designed for in planta detection of the most probable citrus interacting protein partners of P235 and Effector 3. Third, in vitro and in planta studies were performed to show that each of two effectors interacts with and inhibits the functions of multiple citrus proteins belonging to the innate immune pathways. These inhibitory interactions led to a high level of reactive oxygen species (ROS), blocking of bactericidal lipid binding protein (LTP), and induction of premature programmed cell death (PCD), thereby supporting CLas infection and HLB pathogenesis. Finally, an LTP mimic was designed to sequester and block the CLas effector and to rescue the bactericidal activity of LTP.

plant biology↗

bioRxiv2021

Legume plant defenses and nutrients mediate indirect interactions between soil rhizobia and chewing herbivores

Soil bacteria that form mutualisms with plants, such as rhizobia, affects susceptibility of plants to herbivores and pathogens. Soil rhizobia also promote nitrogen fixation, which mediates host nutrient levels and defenses. However, whether aboveground herbivores affect the function of soil rhizobia remains poorly understood. We assessed reciprocal interactions between Sitona lineatus, a chewing herbivore, and pea (Pisum sativum) plants grown with or without rhizobia (Rhizobium leguminosarum biovar viciae). We also examined the underlying plant-defense and nutritional mechanisms of these interactions. In our experiments, soil rhizobia influenced feeding and herbivory by chewing herbivores. Leaf defoliation by S. lineatus was lower on plants treated with rhizobia, but these insects had similar amino acid levels compared to those on un-inoculated plants. Plants grown with soil rhizobia had increased expression of gene transcripts associated with phytohormone-mediated defense, which may explain decreased susceptibility to S. lineatus. Rhizobia also induced expression of gene transcripts associated with physical and antioxidant-related defense pathways in P. sativum. Conversely, S. lineatus feeding reduced the number of root nodules and nodule biomass, suggesting a disruption of the symbiosis between plants and rhizobia. Our study shows that aboveground herbivores can engage in mutually antagonistic interactions with soil microbes mediated through a multitude of plant-mediated pathways.

ecology↗

bioRxiv2021

The YAP/TAZ antagonist, PTPN14, stabilizes SMAD4 through direct interactions in endothelial cells: Implications for Hereditary Hemorrhagic Telangiectasia

Hereditary Hemorrhagic Telangiectasia (HHT) results from germline loss-of-function mutations of ENG, ACVRL1, or SMAD4, encoding TGF{beta}/BMP signaling components. Telangiectasias occur in most patients, and pulmonary, visceral, or cerebral arteriovenous malformations (AVMs) in 20-50% of these. How HHT mutations cause these clinical manifestations and why some patients suffer more serious sequelae than others is unknown. PTPN14 is a genetic modifier of pulmonary AVM incidence, and here we show by gene expression network analysis of a large panel of genetically diverse mouse lung RNA samples, that Ptpn14 is ontologically associated with markers of angiogenesis, vascular remodeling, and BMP/TGF{beta} and Rho kinase signaling. We demonstrate physical interaction between protein tyrosine phosphatase non-receptor, type 14 (PTPN14) and SMAD4 in nucleus and cytoplasm of primary human endothelial cells. PTPN14 suppresses ubiquitination and turnover of SMAD4 to augment tonic SMAD-mediated transcriptional readouts. This is the first report that PTPN14 binds and stabilizes SMAD4, a key component of the HHT signaling pathway. Through this mechanism, and its inhibition of YAP/TAZ signaling, PTPN14 levels may protect against development of AVMs in HHT. We discuss potential druggable targets for HHT within the ENG-ALK1-SMAD4-PTPN14 network. One Sentence SummaryPTPN14 binds and stabilizes SMAD4 to potentiate BMP9 signaling in endothelial cells and components of the PTPN14 network may be drug targets for HHT.

cell biology↗

bioRxiv2021

Computational study on Strontium ion modified Fibronectin-Hydroxyapatite interaction

Protein adsorption is the first key step in cell-material interaction. The initial phase of such adsorption process can only be probed using modelling approaches like molecular dynamics (MD) simulation. Despite a large number of studies on the adsorption behaviour of proteins on different biomaterials including hydroxyapatite (HA); little attention has been paid towards quantitative assessment of the effects of various physicochemical influencers like surface modification, pH, and ionic strength. Among these factors, surface modification through isomorphic substitution of foreign ions inside the apatite structure is of particular interest in the context of protein-HA interaction as it is widely used to tailor the biological response of HA. Given this background, we present here the molecular-level understanding of fibronectin (FN) adsorption mechanism and kinetics on Sr2+-doped HA (001) surface, at 300K by means of all-atom molecular dynamics simulation. Electrostatic interaction involved in adsorption of FN on HA was found to be significantly modified in presence of Sr2+ doping in apatite lattice. In harmony with the published experimental observations, the Sr-doped surface was found to better support FN adhesion compared to pure HA, with 10 mol% Sr-doped HA exhibiting best FN adsorption. Sr2+ ions also influence the stability of the secondary structure of FN, as observed from the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analysis. The presence of Sr2+ enhances the flexibility of specific residues (residue no. 20-44, 74-88) of the FN module. Rupture forces to disentangle FN from the biomaterials surface, obtained from steered molecular dynamics (SMD) simulations, were found to corroborate well with the results of equilibrium MD simulations. One particular observation is that, the availability of RGD motif for the interaction with cell surface receptor integrin is not significantly influenced by Sr2+ substitution. Summarizing, the present work establishes a quantitative foundation towards the molecular basis of the earlier experimentally validated better cytocompatibility of Sr-doped HA. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/461618v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@19614a6org.highwire.dtl.DTLVardef@25b39eorg.highwire.dtl.DTLVardef@13368eborg.highwire.dtl.DTLVardef@2d44ec_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

Comparing Heritability Estimators under Alternative Structures of Linkage Disequilibrium

SNP heritability of a trait is the proportion of its variance explained by the additive effects of the genome-wide single nucleotide polymorphisms (SNPs). The existing approaches to estimate SNP heritability can be broadly classified into two categories. One set of approaches model the SNP effects as fixed effects and the other treats the SNP effects as random effects. These methods make certain assumptions about the dependency among individuals (familial relationship) as well as the dependency among markers (linkage disequilibrium, LD) to provide consistent estimates of SNP heritability as the number of individuals increases. While various approaches have been proposed to account for such dependencies, it remains unclear which estimates reported in the literature are more robust against various model mis-specifications. Here we investigate the impact of different structures of LD and familial relatedness on heritability estimation. We show that the performance of different methods for heritability estimation depends heavily on the structure of the underlying pattern of LD and the degree of relatedness among sampled individuals. However, contrary to the claim in the current literature, we did not find significant differences in the performance of these fixed-SNP-effects and random-SNP-effects approaches. Moreover, we established the equivalence between the two method-of-moments estimators, one from each of these two lines of approaches.

genetics↗

bioRxiv2021

An Empirical Bayes Approach to Estimating Dynamic Models of Co-regulated Gene Expression

Time-course gene expression datasets provide insight into the dynamics of complex biological processes, such as immune response and organ development. It is of interest to identify genes with similar temporal expression patterns because such genes are often biologically related. However, this task is challenging due to the high dimensionality of these datasets and the nonlinearity of gene expression time dynamics. We propose an empirical Bayes approach to estimating ordinary differential equation (ODE) models of gene expression, from which we derive a similarity metric between genes called the Bayesian lead-lag R2 (LLR2). Importantly, the calculation of the LLR2 leverages biological databases that document known interactions amongst genes; this information is automatically used to define informative prior distributions on the ODE models parameters. As a result, the LLR2 is a biologically-informed metric that can be used to identify clusters or networks of functionally-related genes with co-moving or time-delayed expression patterns. We then derive data-driven shrinkage parameters from Steins unbiased risk estimate that optimally balance the ODE models fit to both data and external biological information. Using real gene expression data, we demonstrate that our methodology allows us to recover interpretable gene clusters and sparse networks. These results reveal new insights about the dynamics of biological systems.

genomics↗

bioRxiv2021

Identification of potential carboxylic acid-containing drug candidate to design novel competitive NDM inhibitors: An in-silico approach comprising combined virtual screening and molecular dynamics simulation

Metallo-{beta}-lactamases (MBLs) producing bacteria especially the ones with New Delhi metallo-beta-lactamase-1 (NDM-1) and its variants can potentially hydrolyse all the major {beta}-lactam antibiotics, ultimately escalating anti-microbial resistance world-wide. There is a dearth of approved inhibitors to combat NDM and other MBLs producing bacteria. Hence we focussed to find novel inhibitor(s) in-silico which can potentially suppress the activity of NDM/ MBLs. 2400 compounds were virtually screened to identify a promising carboxylic acid-containing compound (CID-53986787) analogous to NDM antagonist Captopril. Our lead compound can bind adjacent to the active site zinc ions (Zn1 and Zn2) in all highly resistant NDM variants. CID-53986787 possesses ~5-8% higher binding affinity than Captopril, exhibiting molecular interactions with crucial residues that can destabilize the hydrolytic activity of NDM. CID-53986787 was virtually evaluated to ascertain its safe pharmacological/ toxicity profile. Molecular dynamics simulation studies elucidated its stable interaction with the target protein (NDM-1).

bioinformatics↗

bioRxiv2021

Classifying COVID-19 variants based on genetic sequences using deep learning models

The COrona VIrus Disease (COVID-19) pandemic led to the occurrence of several variants with time. This has led to an increased importance of understanding sequence data related to COVID-19. In this chapter, we propose an alignment-free k-mer based LSTM (Long Short-Term Memory) deep learning model that can classify 20 different variants of COVID-19. We handle the class imbalance problem by sampling a fixed number of sequences for each class label. We handle the vanishing gradient problem in LSTMs arising from long sequences by dividing the sequence into fixed lengths and obtaining results on individual runs. Our results show that one-vs-all classifiers have test accuracies as high as 92.5% with tuned hyperparameters compared to the multi-class classifier model. Our experiments show higher overall accuracies for B.1.1.214, B.1.177.21, B.1.1.7, B.1.526, and P.1 on the one-vs-all classifiers, suggesting the presence of distinct mutations in these variants. Our results show that embedding vector size and batch sizes have insignificant improvement in accuracies, but changing from 2-mers to 3-mers mostly improves accuracies. We also studied individual runs which show that most accuracies improved after the 20th run, indicating that these sequence positions may have more contributions to distinguishing among different COVID-19 variants.

bioinformatics↗

bioRxiv2021

Mycobacterium tuberculosis DosS binds H2S through its Fe3+ heme iron to regulate the Dos dormancy regulon

Mycobacterium tuberculosis (Mtb) senses and responds to host-derived gasotransmitters NO and CO via heme-containing sensor kinases DosS and DosT and the response regulator DosR. Hydrogen sulfide (H2S) is an important signaling molecule in mammals, but its role in Mtb physiology is unclear. We have previously shown that exogenous H2S can modulate expression of genes in the Dos dormancy regulon via an unknown mechanism(s). Here, we tested the hypothesis that Mtb senses and responds to H2S via the DosS/T/R system. Using UV-Vis and EPR spectroscopy, we show that H2S binds directly to the ferric (Fe3+) heme of DosS (KD = 5.64 {micro}M) but not the ferrous (Fe2+) form. No interaction with DosT was detected. Thus, the mechanism by which DosS senses H2S is different from that for sensing NO and CO, which bind only the ferrous forms of DosS and DosT. Steered Molecular Dynamics simulations show that H2S, and not the charged HS- species, can enter the DosS heme pocket. We also show that H2S increases DosS autokinase activity and subsequent phosphorylation of DosR, and H2S-mediated increases in Dos regulon gene expression is lost in Mtb lacking DosS. Finally, we demonstrate that physiological levels of H2S in macrophages can induce Dos regulon genes via DosS. Overall, these data reveal a novel mechanism whereby Mtb senses and responds to a third host gasotransmitter, H2S, via DosS-Fe3+. These findings highlight the remarkable plasticity of DosS and establish a new paradigm for how bacteria can sense multiple gasotransmitters through a single heme sensor kinase. Significance StatementHydrogen sulfide (H2S) is an important signaling molecule in eukaryotes and bacteria, and along with CO and NO, is an important part of host defense against Mycobacterium tuberculosis (Mtb). However, the mechanism(s) by which Mtb senses and responds to H2S is unknown. Here, we report that the Mtb heme sensor kinase DosS, a known sensor of CO and NO, is also a sensor of H2S. We found that H2S binds DosS in its ferric (Fe3+) state, which is considered as its inactive state, to induce the Dos dormancy regulon during infection. These data highlight the unusual capacity of Mtb to sense multiple gasotransmitters through a single sensing protein.

biochemistry↗

bioRxiv2021

Vapor mediation as a tool to control micro-nano scale dendritic crystallization and preferential bacterial distribution in drying respiratory droplets

Deposits of biofluid droplets on surfaces (such as respiratory droplets formed during an expiratory event fallen on surfaces) are composed of the water-based salt-protein solution that may also contain an infection (bacterial/viral).The final patterns of the deposit formed are dictated by the composition of the fluid and flow dynamics within the droplet. This work reports the spatio-temporal, topological regulation of deposits of respiratory fluid droplets and control of motility of bacteria by tweaking flow inside droplets using non-contact vapor-mediated interactions. When evaporated on a glass surface, respiratory droplets form haphazard multiscale dendritic, cruciform-shaped precipitates--using vapor mediation as a tool to control these deposits at the level of nano-micro-millimeter scales. Wemorphologically control dendrite orientation, size and subsequently suppress cruciform-shaped crystals. The nucleation sites are controlled via preferential transfer of solutes in the droplets; thus, achieving control over crystal occurrence and growth dynamics. The active living matter like bacteria is also preferentially segregated with controlled motility without attenuation of its viability and pathogenesis. For the first time, we have experimentally presented a proof-of-concept to control the motion of live active matter like bacteria in a near non-intrusive manner. The methodology can have ramifications in biomedical applications like disease detection, controlling bacterial motility, and bacterial segregation.

bioengineering↗

bioRxiv2021

Discovery and mechanism of action of small molecule inhibitors of ceramidases

Sphingolipid metabolism is tightly controlled by enzymes to regulate essential processes such as energy utilisation and cell proliferation. The central metabolite is ceramide, a pro-apoptotic lipid catabolized by ceramidase enzymes to ultimately produce pro-proliferative sphingosine-1-phosphate. Human ceramidases can be soluble proteins (acid and neutral ceramidase) or integral membrane proteins (alkaline ceramidases). Increasing ceramide levels to increase apoptosis has shown efficacy as a cancer treatment using small molecules inhibiting a soluble ceramidase. Due to the transmembrane nature of alkaline ceramidases, no specific small molecule inhibitors have been reported. Here, we report novel fluorescent substrates (FRETceramides) of ceramidases that can be used to monitor enzyme activity in real-time. We use FRETceramides to discover the first drug-like inhibitors of alkaline ceramidase 3 (ACER3) which are active in cell-based assays. Biophysical characterization of enzyme:inhibitor interactions reveal a new paradigm for inhibition of lipid metabolising enzymes with non-lipidic small molecules. Table of contents summaryUse of synthetic fluorescent ceramide molecules allows the discovery of the first selective drug-like small molecule inhibitors for alkaline ceramidase 3, an intra-membrane enzyme involved in sphingolipid metabolism in health and disease.

biochemistry↗

bioRxiv2021

An automated platform for structural analysis of membrane proteins through serial crystallography

Membrane proteins are central to many pathophysiological processes yet remain very difficult to analyze at a structural level. Moreover, high-throughput structure-based drug discovery has not yet been exploited for membrane proteins due to lack of automation. Here, we present a facile and versatile platform for in meso membrane protein crystallization, enabling rapid atomic structure determination at both cryogenic and room temperature and in a single support. We apply this approach to two human integral membrane proteins, which allowed us to capture different conformational states of intramembrane enzyme-product complexes and analyze the structural dynamics of the ADIPOR2 integral membrane protein. Finally, we demonstrate an automated pipeline combining high-throughput microcrystal soaking, automated laser-based harvesting and serial crystallography enabling screening of small molecule libraries with membrane protein crystals grown in meso. This approach brings badly needed automation for this important class of drug targets and enables high-throughput structure-based ligand discovery with membrane proteins. HighlightsO_LIA fully automated, online workflow enables rapid determination of membrane protein structures by serial X-ray crystallography (SSX). C_LIO_LIHigh resolution room temperature and cryogenic structures of ADIPOR2 provide insights into the dynamic nature of receptor:ligand interactions. C_LIO_LIA web-based application allows remote user-guided experimental design and execution. C_LIO_LIAn automated SSX-based ligand discovery pipeline for integral membrane proteins is introduced. C_LI

biochemistry↗

bioRxiv2021

Spatiotemporal evaporating droplet dynamics on fomites enhances long term bacterial pathogenesis

Naturally drying bacterial droplets on inanimate surfaces representing fomites are the most consequential mode for transmitting infection through oro-fecal route. We provide a multiscale holistic approach to understand flow dynamics induced bacterial pattern formation on fomites leading to pathogenesis. The most virulent gut pathogen, Salmonella Typhimurium (STM), typically found in contaminated food and water, is used as model system in the current study. Evaporation-induced flow in sessile droplets facilitates the transport of STM, forming spatio-temporally varying bacterial deposition patterns based on droplet mediums nutrient scale. Mechanical and low moisture stress in the drying process, reduced bacterial viability but interestingly induced hyper-proliferation of STM in macrophages, augmenting virulence in fomites. In vivo studies of fomites in mice confirm that STM maintains virulence. This work demonstrates that stressed bacterial deposit morphologies formed over small timescale (minutes) on organic and inorganic surfaces, plays significant role in enhancing fomites pathogenesis over hours and days.

microbiology↗

bioRxiv2021

Rapid Estimation of SNP Heritability using Predictive Process approximation in Large scale Cohort Studies

With the advent of high throughput genetic data, there have been attempts to estimate heritability from genome-wide SNP data on a cohort of distantly related individuals using linear mixed model (LMM). Fitting such an LMM in a large scale cohort study, however, is tremendously challenging due to its high dimensional linear algebraic operations. In this paper, we propose a new method named PredLMM approximating the aforementioned LMM motivated by the concepts of genetic coalescence and gaussian predictive process. PredLMM has substantially better computational complexity than most of the existing LMM based methods and thus, provides a fast alternative for estimating heritability in large scale cohort studies. Theoretically, we show that under a model of genetic coalescence, the limiting form of our approximation is the celebrated predictive process approximation of large gaussian process likelihoods that has well-established accuracy standards. We illustrate our approach with extensive simulation studies and use it to estimate the heritability of multiple quantitative traits from the UK Biobank cohort.

bioinformatics↗

bioRxiv2021

Can charge-reversal be considered as a strategy for attaining thermal stability in proteins?

Do charge reversal mutations (CRM) naturally occur in mesophilic-thermophilic/hyperthermophilic (M-T/HT) orthologous proteins? Do they contribute to thermal stability by altering charge-charge interactions? A careful investigation on 1550 M-T/HT orthologous protein pairs with remarkable structural and topological similarity extracts the role of buried and partially exposed CRMs in enhancing thermal stability. Our findings could assist in engineering thermo-stable variants of proteins. SIGNIFICANCEProtein engineering is one of the hot topics for decades specifically for its applications in different fields like de-novo protein design, directed evolution, making highly stable variants for food and drug industry etc. Proteins from organisms living in extreme environments are therefore a matter of common interest for scientists from different disciplines. Over three decades of study has already found several sequence and structural adaptations related to thermal stability, while charge reversal study remains ignored to a large extent. Influenced by natures strategy, our study provides a systemic understanding of how proper designing of few partially exposed and buried CRMs significantly contributes to thermal stability by altering the short distance electrostatic interactions.

bioinformatics↗

bioRxiv2021

Ssl2/TFIIH Function in Transcription Start Site Scanning by RNA Polymerase II in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, RNA Polymerase II (Pol II) selects transcription start sites (TSS) by a unidirectional scanning process. During scanning, a preinitiation complex (PIC) assembled at an upstream core promoter initiates at select positions within a window [~]40-120 basepairs downstream. Several lines of evidence indicate that Ssl2, the yeast homolog of XPB and an essential and conserved subunit of the general transcription factor (GTF) TFIIH, drives scanning through its DNA-dependent ATPase activity, therefore potentially controlling both scanning rate and scanning extent (processivity). To address questions of how Ssl2 functions in promoter scanning and interacts with other initiation activities, we leveraged distinct initiation-sensitive reporters to identify novel ssl2 alleles. These ssl2 alleles, many of which alter residues conserved from yeast to human, confer either upstream or downstream TSS shifts at the model promoter ADH1 and genome-wide. Specifically, tested ssl2 alleles alter TSS selection by increasing or narrowing the distribution of TSSs used at individual promoters. Genetic interactions of ssl2 alleles with other initiation factors are consistent with ssl2 allele classes functioning through increasing or decreasing scanning processivity but not necessarily scanning rate. These alleles underpin a residue interaction network that likely modulates Ssl2 activity and TFIIH function in promoter scanning. We propose that the outcome of promoter scanning is determined by two functional networks, the first being Pol II activity and factors that modulate it to determine initiation efficiency within a scanning window, and the second being Ssl2/TFIIH and factors that modulate scanning processivity to determine the width of the scanning widow.

molecular biology↗