Biology subjects

Tattikota, S. G.

Publications and source records attributed to Tattikota, S. G..

9 recordsLinked to original sources

bioRxiv2026

MERFISH 2.0, an ultra-sensitive single-cell spatial transcriptomics imaging chemistry across diverse tissue types

Spatial transcriptomics has emerged as a transformative approach for elucidating tissue architecture, cellular heterogeneity, and disease mechanisms by preserving the spatial context of gene expression in cells. Despite these advances, many spatial transcriptomic methods underperform in archival or clinically relevant specimens, particularly formalin-fixed, paraffin-embedded (FFPE) tissues, where RNA degradation and crosslinking hinder transcript detection. To address these challenges, we developed Multiplexed Error Robust Fluorescence In Situ Hybridization 2.0 (MERFISH 2.0), an optimized spatial transcriptomic imaging chemistry to enhance profiling of fragmented and highly crosslinked RNA. Across diverse human and mouse tissues preserved as fresh-frozen, fixed-frozen, and FFPE specimens, MERFISH 2.0 substantially increased transcript detection sensitivity by up to [~]8-fold relative to MERFISH 1.0 while preserving quantitative concordance (Pearson r [≥] 0.8 across tissues). In archived fresh-frozen human brain samples, MERFISH 2.0s enhanced sensitivity improved transcript recovery, enhanced cell type resolution and spatial analyses. In low quality archival FFPE human breast cancer specimen, MERFISH 2.0 revealed additional cell populations, novel cell clusters, refined tumor-immune architecture, and increased detection of gene-gene and cell-cell interactions relative to MERFISH 1.0, underscoring the impact of improved sensitivity on downstream spatial analysis. By substantially expanding robust transcript detection to degraded and archival samples, MERFISH 2.0 enables scalable, cohort-level spatial transcriptomic analysis across clinically relevant tissue collections.

genomics↗

bioRxiv2025

Multi-omic mapping of Drosophila protein secretomes reveals tissue-specific origins and inter-organ trafficking

Secreted proteins regulate many aspects of animal biology and are attractive targets for biomarkers and therapeutics. However, comprehensively identifying the "secretome", along with their tissues of origin, remains extremely challenging. To address this, we employed multiple omics methods to define a tissue-secretome map of 535 blood plasma proteins derived from specific cell-types and organs in Drosophila melanogaster. This map was enabled by methodological improvements including a collection of transgenic flies to label endogenous secreted proteins in 10 major tissue types, large-scale blood isolation, whole animal snRNA-seq, and a collection of 40 knock-in strains. Using this map, we discover surprising findings about circulating proteins: most originate from specific tissues including unusual sources (e.g. glia), many are uncharacterized, and some are shed ectodomains of transmembrane proteins. In addition, in vivo experiments revealed circulating proteins with remarkably tissue-specific expression, as well as proteins that are deposited in a different tissue from where they are synthesized, suggesting potential inter-organ functions. Our secretome map will serve as a resource to investigate blood protein function, discover novel tissue-tissue communication signals, and mine for homologues of human biomarkers.

genomics↗

bioRxiv2022

Optimal transport analysis of single-cell transcriptomics directs hypotheses prioritization and validation

The explosive growth of regulatory hypotheses from single-cell datasets demands accurate prioritization of hypotheses for in vivo validation. However, current computational methods emphasize overall accuracy in regulatory network reconstruction rather than prioritizing a limited set of causal transcription factors (TFs) that can be feasibly tested. We developed Haystack, a hybrid computational-biological algorithm that combines active learning and the concept of optimal transport theory to nominate and validate high-confidence causal hypotheses. Our novel approach efficiently identifies and prioritizes transient but causally-active TFs in cell lineages. We applied Haystack to single-cell observations, guiding efficient and cost-effective in vivo validations that reveal causal mechanisms of cell differentiation in Drosophila gut and blood lineages. Notably, all the TFs shortlisted for the final, imaging-based assays were validated as drivers of differentiation. Haystacks hypothesis-prioritization approach will be crucial for validating concrete discoveries from the increasingly vast collection of low-confidence hypotheses from single-cell transcriptomics.

bioinformatics↗

bioRxiv2022

Modeling exercise using optogenetically contractible Drosophila larvae

The pathophysiological effects of a number of metabolic and age-related disorders can be prevented to some extent by exercise and increased physical activity. However, the molecular mechanisms that contribute to the beneficial effects of muscle activity remain poorly explored. Availability of a fast, inexpensive, and genetically tractable model system for muscle activity and exercise will allow the rapid identification and characterization of molecular mechanisms that mediate the beneficial effects of exercise. Here, we report the development and characterization of an optogenetically-inducible muscle contraction (OMC) model in Drosophila larvae that we used to study acute exercise-like physiological responses. To characterize muscle-specific transcriptional responses to acute exercise, we performed bulk mRNA-sequencing, revealing striking similarities between acute exercise-induced genes in flies and those previously identified in humans. Our larval muscle contraction model opens a path for rapid identification and characterization of exercise-induced factors.

genomics↗

bioRxiv2021

Fly Cell Atlas: a single-cell transcriptomic atlas of the adult fruit fly

The ability to obtain single cell transcriptomes for stable cell types and dynamic cell states is ushering in a new era for biology. We created the Tabula Drosophilae, a single cell atlas of the adult fruit fly which includes 580k cells from 15 individually dissected sexed tissues as well as the entire head and body. Over 100 researchers from the fly community contributed annotations to >250 distinct cell types across all tissues. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types that are shared between tissues, such as blood and muscle cells, allowed the discovery of rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the entire Drosophila community and serves as a comprehensive reference to study genetic perturbations and disease models at single cell resolution.

genomics↗

bioRxiv2021

DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, called DRscDB (https://www.flyrnai.org/tools/single_cell/web/) to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and the relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. DRscDB serves as a web-based user interface that allows users to mine, utilize and compare gene expression data pertaining to scRNA-seq datasets from the published literature.

bioinformatics↗

bioRxiv2020

Single-cell transcriptome maps of myeloid blood cell lineages in Drosophila

Drosophila lymph gland, the larval hematopoietic organ comprised of prohemocytes and hemocytes, has been a valuable model for understanding mechanisms underlying hematopoiesis and immunity. Three types of mature hemocytes have been characterized in the lymph gland: plasmatocytes, lamellocytes, and crystal cells, which are analogous to vertebrate myeloid cells. Here, we used single-cell RNA sequencing to comprehensively analyze heterogeneity of developing hemocytes in the lymph gland, and discovered novel hemocyte types, stem-like prohemocytes, and intermediate prohemocytes. Additionally, we identified the emergence of the lamellocyte lineage following active cellular immunity caused by wasp infestation. We unraveled similarities and differences between embryonically derived- and larval lymph gland hemocytes. Finally, the comparison of Drosophila lymph gland hemocytes and human immune cells highlights similarities between prohemocytes and hematopoietic stem cell, and between mature hemocytes and myeloid cells across species. Altogether, our study provides detailed insights on the development and evolution of hematopoiesis at single-cell resolution.

developmental biology↗

bioRxiv2019

A single-cell survey of Drosophila blood

Drosophila blood cells, called hemocytes, are classified into plasmatocytes, crystal cells, and lamellocytes based on the expression of a few marker genes and cell morphologies, which are inadequate to classify the complete hemocyte repertoire. Here, we used single-cell RNA sequencing (scRNA-seq) to map hemocytes across different inflammatory conditions in larvae. We resolved plasmatocytes into different states based on the expression of genes involved in cell cycle, antimicrobial response, and metabolism together with the identification of intermediate states. Further, we discovered rare subsets within crystal cells and lamellocytes that express fibroblast growth factor (FGF) ligand branchless and receptor breathless, respectively. We demonstrate that these FGF components are required for mediating effective immune responses against parasitoid wasp eggs, highlighting a novel role for FGF signaling in inter-hemocyte crosstalk. Our scRNA-seq analysis reveals the diversity of hemocytes and provides a rich resource of gene expression profiles for a systems-level understanding of their functions. HighlightsO_LIscRNA-seq of Drosophila blood recovers plasmatocytes, crystal cells, and lamellocytes C_LIO_LIscRNA-seq identifies different plasmatocyte states based on the expression of genes involved in cell cycle regulation, antimicrobial response, and metabolism C_LIO_LIPseudotemporal ordering of single cells identifies crystal cell and lamellocyte intermediate states C_LIO_LIscRNA-seq uncovers a novel role for FGF signaling in inter-hemocyte crosstalk C_LI

immunology↗

bioRxiv2018

A cell atlas of the adult Drosophila midgut

Studies of the adult Drosophila midgut have provided a number of insights on cell type diversity, stem cell regeneration, tissue homeostasis and cell fate decision. Advances in single-cell RNA sequencing (scRNA-seq) provide opportunities to identify new cell types and molecular features. We used inDrop to characterize the transcriptome of midgut epithelial cells and identified 12 distinct clusters representing intestinal stem cells (ISCs), enteroblasts (EBs), enteroendocrine cells (EEs), enterocytes (ECs) from different regions, and cardia. This unbiased approach recovered 90% of the known ISCs/EBs markers, highlighting the high quality of the dataset. Gene set enrichment analysis in conjunction with electron micrographs revealed that ISCs are enriched in free ribosomes and possess mitochondria with fewer cristae. We demonstrate that a subset of EEs in the middle region of the midgut expresses the progenitor marker esg and that individual EEs are capable of expressing up to 4 different gut hormone peptides. We also show that the transcription factor klumpfuss (klu) is expressed in EBs and functions to suppress EE formation. Lastly, we provide a web-based resource for visualization of gene expression in single cells. Altogether, our study provides a comprehensive resource for addressing novel functions of genes in the midgut epithelium.

genetics↗