Biology subjects

Narayanan, A.

Publications and source records attributed to Narayanan, A..

40 records · Page 3Linked to original sources

bioRxiv2019

Identification of anonymous DNA using genealogical triangulation

AO_SCPLOWBSTRACTC_SCPLOWConsumer genetics databases hold dense genotypes of millions of people, and the number is growing quickly [1] [2]. In 2018, law enforcement agencies began using such databases to identify anonymous DNA via long-range familial searches. We show that this technique is far more powerful if combined with a genealogical database of the type collected by online ancestry services. We present a "genealogical triangulation" algorithm and study its effectiveness on simulated datasets. We show that for over 50% of targets, their anonymous DNA can be identified (matched to the correct individual or same-sex sibling) when the genetic database includes just 1% of the population. We also show the effectiveness of "snowball identification" in which a successful identification adds to the genetic genealogical database, increasing the identification accuracy for future instances. We discuss our techniques potential to enhance law enforcement capabilities as well as its privacy risks.

genomics↗

bioRxiv2018

Cryo-EM structure of Escherichia coli σ70 RNAP and promoter DNA complex revealed a role of σ nonconserved region during the open complex formation

First step of gene expression is transcribing the genetic information stored in DNA to RNA by the transcription machinery including RNA polymerase (RNAP). In Escherichia coli, a primary {sigma}70 factor form the RNAP holoenzyme to express housekeeping genes. The {sigma}70 contains a large insertion at between the conserved regions 1.2 and 2.1, the {sigma} non-conserved region ({sigma}NCR), but its function remains to be elucidated. In this study, we determined the cryo-EM structures of the E. coli RNAP {sigma}70 holoenzyme and its complex with promoter DNA (open complex, RPo) at 4.2 and 5.75 [A] resolutions, respectively, to reveal native conformations of RNAP and DNA. The RPo structure presented here found an interaction between R157 residue in the {sigma}NCR and promoter DNA just upstream of the -10 element, which was not observed in a previously determined E. coli RNAP transcription initiation complex (RPo plus short RNA) structure by X-ray crystallography due to restraint of crystal packing effect. Disruption of the {sigma}NCR and DNA interaction by the amino acid substitution (R157E) influences the DNA opening around the transcription start site and therefore decreases the transcription activity of RNAP. We propose that the {sigma}NCR and DNA interaction is conserved in proteobacteria and RNAP in other bacteria replace its role with a transcription factor.

molecular biology↗

bioRxiv2017

A First Order Phase Transition Underlies the Formation of Sub-Diffractive Protein Aggregates in Mammalian Cells

Failure in protein quality control can often lead to protein aggregation, yet in neuro-degenerative diseases, by the time aggregates can be seen, the cells have advanced well into the disease pathology. Here, we develop a quantitative imaging approach to study the protein aggregation process in living mammalian cells with unprecedented spatio-temporal resolution. We find that sub-diffractive precursor aggregates may form even in untreated cells, and their size distribution is exactly as predicted for a system undergoing a first order phase transition. Practically, this implies that as soon as aggregates reach a critical size (Rc = 162 {+/-} 4 nm untreated cells), they will spontaneously grow into large inclusions. Our data suggest that a previously uncharacterized, RuvBL1 dependent mechanism clears aggregates above the critical size. Our study unveils the existence of sub-diffractive aggregates in living cells; and the strong agreement between cellular data and a nucleation theory, based on first order phase transition, provides insight into regulatory steps in the early stages of aggregate formation in vivo.

biophysics↗

bioRxiv2017

qSR: A software for quantitative analysis of single molecule and super-resolution data

Single-molecule based super-resolution microscopy (Betzig et al., 2006; Hess et al., 2006; Rust et al., 2006) provides insight into the spatiotemporal organization and dynamics of biomolecules at the length scale of ten to hundreds of nanometers, which is most relevant to protein clustering in a broad range of cellular processes. A series of quantitative analysis approaches have been developed to infer the characteristic size of protein clustering via pair correlation analysis (Sengupta et al., 2013; Sengupta et al., 2011; Veatch et al., 2012) or to merge multiple blinking localizations from single fluorophores (Annibale et al., 2011), to identify clusters based on density of detections (Ester, 1996), and to measure temporal dynamics of protein clustering in living cells (Cho et al., 2016a; ...

biophysics↗