Biology subjects

Kiran, M.

Publications and source records attributed to Kiran, M..

5 recordsLinked to original sources

bioRxiv2026

From APTs to advanced persistent biological threats (APBTs): a taxonomy and large-scale metadata audit of genomic surveillance infrastructure

Open genomic repositories have become critical infrastructure for pathogen surveillance, variant tracking, outbreak reconstruction, and public health decision making. However, many of these repositories were designed to support rapid scientific data sharing rather than adversarial verification, creating potential security gaps. This paper introduces Advanced Persistent Biological Threats (APBTs), as a framework for understanding how malicious cyber biological actors can gradually disrupt genomic surveillance without entering a laboratory or releasing a biological agent. Instead of altering biological material, an attacker targets the sequence data, metadata, reference datasets, and analytical models used by surveillance systems. We present, to our knowledge, the first integrated multilayer taxonomy of APBTs, structured around a four phase lifecycle, and investigate whether the metadata weaknesses identified by this framework are present in an operational genomic repository. To assess this, we audited 100,000 SARS-CoV-2 BioSample records obtained from the NCBI. A framework of 23 checks was applied across five metadata layers: temporal, geographic, host and specimen, provenance, and technical metadata. Every record triggered at least one APBT relevant metadata vulnerability indicator, with a mean of 7.34 indicators per record (SD = 1.34). Overall, 97.3% of records were classified in the High or Critical severity categories. Every record also contained at least one indicator in both the provenance and technical metadata layers. These results largely reflect the optional status of several fields in the current BioSample submission model rather than isolated errors by individual data contributors. Temporal and geographic information was comparatively complete, while fields needed for provenance reconstruction, chain of custody assessment, technical validation, and analytical interpretation were frequently missing. These findings do not indicate deliberate manipulation. However, the structural incompleteness of BioSample metadata creates vulnerabilities that an adversary can exploit to introduce poisoned, misleading, or weakly traceable metadata into genomic repositories. As a result, maliciously altered metadata can appear plausible, remain undetected, and influence downstream genomic analysis and surveillance. The findings therefore show that widely used pathogen genomic repositories already contain structural weaknesses that can support metadata poisoning as part of an APBT operation.

genomics↗

bioRxiv2021

Comparative analysis of Pure Hubs and Pure Bottlenecks in Human Protein-protein Interaction Networks

Bottlenecks and hubs form a set of topologically important nodes in a network. In this communication, we have made a detailed investigation on hubs and bottlenecks in human protein-protein interaction networks. We find that, three distinct groups exist which we refer to as: a) pure hubs (PHs, nodes having high degree but low betweenness values), b) mix proteins (MXs, nodes having both high degree and high betweenness values) and c) pure bottlenecks (PBs, nodes having high betweenness values but low degree values). Our investigations have revealed that pure hubs, as compared with MXs and PBs, (i) are more disordered, (ii) have higher potential to bind to multiple partners, (iii) are enriched with essential proteins as well as enriched with a higher number of splice variants. The MX proteins, as compared with PHs and PBs, (i) show slower evolutionary patterns, (ii) are involved in multiple pathways, (iii) enriched with the products of genes associated with various diseases and (iv) are more often targeted by bacteria, viruses, protozoa, and fungi pathogens. PBs, as compared with the PHs and MXs, (i) are associated with cancer genes and (ii) are the targets or the nearest neighbors of the targets of most of the approved drugs. Furthermore, our study revealed that these three categories of proteins are involved in distinct functional roles; PHs are involved in housekeeping processes such as transcription and replication; MXs proteins are involved in core signaling pathways whereas PBs are involved in signal transduction processes. Our work, therefore, has identified the distinct characteristics features associated with pure hubs, mix proteins and pure bottlenecks and thus helps in prioritizing proteins based on their degree and betweenness centrality values.

systems biology↗

bioRxiv2018

The Germline Variants rs61757955 and rs34988193 are Predictive of Survival in Low Grade Glioma Patients

AbstractLow grade gliomas are invasive brain tumors that are difficult to completely resect neurosurgically. They often recur following resection and progress, resulting in death. Although previous studies have shown that specific germline variants increase the risk of tumor formation, no previous study has screened many germline variants to identify variants predictive of survival in glioma patients. In this study, we present an approach to identify the small fraction of prognostic germline variants from the pool of over four million variants that we variant called in The Cancer Genome Atlas whole exome sequencing and RNA sequencing datasets. We identified two germline variants that are predictive of poor patient outcomes by Cox regression, controlling for eleven covariates. rs61757955 is a germline variant found in the 3 UTR of GRB2 associated with increased KRAS signaling, CIC mutations, and 1p/19q co-deletion. rs34988193 is a germline variant found in the tumor suppressor gene ANKDD1a that causes an amino acid change from lysine to glutamate. This variant was found to be predictive of poor prognosis in two independent low grade glioma datasets and is predicted to be within the top 0.06% of deleterious mutations across the human genome. The wild type residue is conserved in all 22 other species with a homologous protein.\n\nImplicationsThis is the first study presenting an approach to screening many germline variants to identify variants predictive of survival and our application of this methodology revealed the germline variants rs61757955 and rs34988193 as being predictive of survival in low grade glioma patients.

cancer biology↗

bioRxiv2018

A prognostic signature for lower-grade gliomas based on expression of long noncoding RNAs

Diffuse low-grade and intermediate-grade gliomas (together known as lower-grade gliomas, WHO grade II and III) develop in the supporting glial cells of brain and are the most common types of primary brain tumor. Despite a better prognosis for lower-grade gliomas, 70% of patients undergo high-grade transformation within 10 years, stressing the importance of better prognosis. Long non-coding RNAs (lncRNAs) are gaining attention as potential biomarkers for cancer diagnosis and prognosis. We have developed a computational model, UVA8, for prognosis of lower-grade gliomas by combining lncRNA expression, Cox regression and L1-LASSO penalization. The model was trained on a subset of patients in TCGA. Patients in TCGA, as well as a completely independent validation set (CGGA) could be dichotomized based on their risk score, a linear combination of the level of each prognostic lncRNA weighted by its multivariable cox regression coefficient. UVA8 is an independent predictor of survival and outperforms standard epidemiological approaches and previous published lncRNA-based predictors as a survival model. Guilt-by-association studies of the lncRNAs in UVA8, all of which predict good outcome, suggest they have a role in suppressing interferon stimulated response and epithelial to mesenchymal transition. The expression levels of 8 lncRNAs can be combined to produce a prognostic tool applicable to diverse populations of glioma patients. The 8 lncRNA (UVA8) based score can identify grade II and grade III glioma patients with poor outcome and thus identify patients who should receive more aggressive therapy at the outset.

genomics↗

bioRxiv2017

Global Gene Repression By Dicer-Independent tRNA Fragments

tRNA derived RNA fragments (tRFs) is an emerging group of small RNAs as abundant as miRNAs, and yet their roles are not well understood. Here, we focus on endogenous tRFs (18-22 bases) derived from 3 end of human mature tRNAs (tRF-3) and their functions in gene repression. tRF-3 levels increase upon parental tRNA over-expression or tRNA induction by c-Myc oncogene activation. Elevated tRF-3 levels lead to repression of target genes with a sequence complementary to the tRF-3 in the 3 UTR. The tRF-3-mediated repression is Dicer-independent, Argonaute-dependent and the targets are recognized by 5 seed sequence rules similar to miRNAs. Furthermore, tRF-3s associate with GW proteins in P-bodies. RNA-seq identifies the endogenous target genes of tRF-3s that are specifically repressed upon tRF-3 induction. Overall, our analysis shows Dicer-independent tRF-3s, generated upon tRNA upregulation such as c-Myc overexpression, regulate gene expression globally through Argounate via seed sequence matches.

molecular biology↗