Biology subjects

Kosuri, S.

Publications and source records attributed to Kosuri, S..

6 recordsLinked to original sources

bioRxiv2018

A Scalable, Multiplexed Assay for Decoding Receptor-Ligand Interactions

Chemicals such as drugs, hormones, and odorants can have many potential interactions with endogenous targets, and uncovering these relationships is critical for understanding and modulating function. Mammalian olfactory receptors (ORs), a large family of G protein-coupled receptors, mediate olfaction through activation by small molecules. Each OR can respond to many odorants, and vice versa, making exploring this space one interaction at a time difficult. We developed a high-throughput receptor screening platform in human cell lines to screen libraries of chemicals against a multiplexed library of receptors using next-generation sequencing of barcoded genetic reporters. We screened three concentrations of 181 odorants, where in each well we record the activity of 39 ORs simultaneously, and identified 79 novel associations, including ligands for 15 orphan receptors. This platform allows the cost-effective mapping of large chemical libraries to receptor repertoires at scale.

biochemistry↗

bioRxiv2017

Systematic Dissection of Sequence Elements Controlling σ70 Promoters Using a Genomically-Encoded Multiplexed Reporter Assay in E. coli

Promoters are the key drivers of gene expression and are largely responsible for the regulation of cellular responses to time and environment. In E. coli, decades of studies have revealed most, if not all, of the sequence elements necessary to encode promoter function. Despite our knowledge of these motifs, it is still not possible to predict the strength and regulation of a promoter from primary sequence alone. Here we develop a novel multiplexed assay to study promoter function in E. coli by building a site-specific genomic recombination-mediated cassette exchange (RMCE) system that allows for the facile construction and testing of large libraries of genetic designs integrated into precise genomic locations. We build and test a library of 10,898 {sigma}70 promoter variants consisting of all combinations of a set of eight -35 elements, eight -10 elements, three UP elements, eight spacers, and eight backgrounds. We find that the -35 and -10 sequence elements can explain approximately 74% of the variance in promoter strength within our dataset using a simple log-linear statistical model. Simple neural network models explain greater than 95% of the variance in our dataset by capturing nonlinear interactions with the spacer, background, and UP elements.

molecular biology↗

bioRxiv2017

Large-scale screening of rare genetic variants in humans reveals frequent splicing disruptions

Any individuals genome contains [~]4-5 million genetic variants that differ from reference, and understanding how these variants give rise to trait diversity and disease susceptibility is a central goal of human genetics1. A vast majority (96-99%) of an individuals variants are common, though at a population level the overwhelming majority of variants are rare2-5. Because of their scarcity in an individuals genome, rare variants that play important roles in complex traits are likely to have large functional effects6,7. Mutations that cause an exon to be skipped can have severe functional consequences on gene function, and many known disease-causing mutations reduce or eliminate exon recognition8. Here we explore the extent to which rare genetic variation in humans results in near complete loss of exon recognition. We developed a Multiplexed Functional Assay of Splicing using Sort-seq (MFASS) that allows us to measure exon inclusion in thousands of human exons and surrounding intronic sequence simultaneously. We assayed 27,733 extant variants in the Exome Aggregation Consortium (ExAC)9 within or adjacent to 2,339 human exons, and found that 3.8% (1,050) of the variants, almost all of which were extremely rare, led to large-effect defects in exon recognition. Importantly, we find that 83% of these splice-disrupting variants (SDVs) are located outside of canonical splice sites, are distributed evenly across distinct exonic and intronic regions, and are difficult to predict a priori. Our results indicate that loss of exon recognition is an important and underappreciated means by which rare variants exert large functional effects, and that MFASS enables their empirical assessment for splicing defects at scale.

genetics↗

bioRxiv2017

Multiplexed Gene Synthesis in Emulsions for Exploring Protein Functional Landscapes

Next-generation sequencing has engendered an expanding suite of functional assays that can test sequence-function relationships at unprecedented scales in pooled formats (multiplex). Such assays are currently constrained by the short length of oligonucleotide (oligo) pools, which limit potential applications. Here we report a simple, low-cost, and scalable method called DropSynth that assembles gene libraries from oligo pools for use in multiplexed functional assays. DropSynth utilizes a library of barcoded beads to isolate and concentrate oligos needed for a genes synthesis in a pooled format. These bead-bound oligos are then emulsified, processed, and assembled into genes within the emulsion droplets. We synthesized ~1000 phylogenetically diverse orthologs of phosphopantetheine adenylyltransferase (PPAT) and tested their fitness in a multiplexed functional assay. While the majority of orthologs complement, those that do not are broadly distributed across the phylogenetic tree. Synthetic errors in our assemblies allow us to explore local landscapes around the designed orthologs revealing constrained mutations for complementing orthologs as well as gain-of-function mutations for low-fitness orthologs. This broad mutational scanning approach is complementary to deep mutational scanning and helps us understand proteins by probing evolutionarily divergent sequences that share function.

biochemistry↗

bioRxiv2017

Highly parallel genome variant engineering with CRISPR/Cas9 in eukaryotic cells

Direct measurement of functional effects of DNA sequence variants throughout a genome is a major challenge. We developed a method that uses CRISPR/Cas9 to engineer many specific variants of interest in parallel in the budding yeast Saccharomyces cerevisiae, and to screen them for functional effects. We used the method to examine the functional consequences of premature termination codons (PTCs) at different locations within all annotated essential genes in yeast. We found that most PTCs were highly deleterious unless they occurred close to the C-terminal end and did not interrupt an annotated protein domain. Surprisingly, we discovered that some putatively essential genes are dispensable, while others have large dispensable regions. This approach can be used to profile the effects of large classes of variants in a high-throughput manner.

genomics↗

bioRxiv2017

A systematic comparison of error correction enzymes by next-generation sequencing

Gene synthesis, the process of assembling gene-length fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality, and cost of gene synthesis is limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment and throughput. Here we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in a model gene assembly and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G [->] G/C transversions whereas T7 Endonuclease I preferentially corrects A/T [->] T/A transversions. More generally, this experimental and computational pipeline is a fast, scalable, and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.

synthetic biology↗