Biology subjects

Somasundaran, M.

Publications and source records attributed to Somasundaran, M..

4 recordsLinked to original sources

bioRxiv2024

Virion-associated influenza hemagglutinin clusters upon sialic acid binding visualized by cryo-electron tomography

Influenza viruses are enveloped, negative sense single-stranded RNA viruses covered in a dense layer of glycoproteins. Hemagglutinin (HA) accounts for 80-90% of influenza glycoprotein and plays a role in host cell binding and membrane fusion. While previous studies have characterized structures of receptor-free and receptor-bound HA in vitro, the effect of receptor binding on HA organization and structure on virions remains unknown. Here, we used cryo-electron tomography (cryoET) to visualize influenza virions bound to a sialic acid receptor mimic. Overall, receptor binding did not result in significant changes in viral morphology; however, we observed rearrangements of HA trimer organization and orientation. Compared to the even inter-glycoprotein spacing of unliganded HA trimers, receptor binding promotes HA trimer clustering and formation of a triplet of trimers. Subtomogram averaging and refinement yielded 8-10 [A] reconstructions that allowed us to visualize specific contacts between HAs from neighboring trimers and identify molecular features that mediate clustering. Taken together, we present new structural evidence that receptor binding triggers clustering of HA trimers, revealing an additional layer of HA dynamics and plasticity.

biophysics↗

bioRxiv2022

Cell culture model system utilizing engineered A549 cells to express high levels of ACE2 and TMPRSS2 for investigating SARS-CoV-2 infection and antivirals

Novel pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to pose an imminent global threat since its initial outbreak in December 2019. A simple in vitro model system using cell lines highly susceptible to SARS-CoV-2 infection are critical to facilitate the study of the virus cycle and to discover effective antivirals against the virus. Human lung alveolar A549 cells are regarded as a useful and valuable model for respiratory virus infection. However, SARS-CoV-2 uses the ACE2 as receptor for viral entry and the TMPRSS2 to prime the Spike protein, both of which are negligibly expressed in A549 cells. Here, we report the generation of a robust human lung epithelial cell-based model by transducing ACE2 and TMPRSS2 into A549 cells and show that the ACE2 enriched A549ACE2/TMPRSS2 cells (ACE2plus) and its single-cell-derived subclone (ACE2plusC3) are highly susceptible to SARS-CoV-2 infection. These engineered ACE2plus showed higher ACE2 and TMPRSS2 mRNA expression levels than currently used Calu3 and commercial A549ACE2/TMPRSS2 cells. ACE2 and TMPRSS2 proteins were also highly and ubiquitously expressed in ACE2plusC3 cells. Additionally, antiviral drugs like Camostat mesylate, EIDD-1931, and Remdesivir strongly inhibited SARS-CoV-2 replication. Notably, multinucleated syncytia, a clinical feature commonly observed in severe COVID-19 patients was induced in ACE2plusC3 cells either by virus infection or by overexpressing the Spike proteins of different variants of SARS-CoV-2. Syncytial process was effectively blocked by the furin protease inhibitor, Decanoyl-RVKR-CMK. Taken together, we have developed a robust human A549 lung epithelial cell-based model that can be applied to probe SARS-CoV-2 replication and to facilitate the discovery of SARS-CoV-2 inhibitors.

cell biology↗

bioRxiv2021

Quantitative Structural Analysis of Influenza Virus by Cryo-electron Tomography and Convolutional Neural Networks

Influenza viruses pose severe public health threats; they cause millions of infections and tens of thousands of deaths annually in the US. Influenza viruses are extensively pleomorphic, in both shape and size as well as organization of viral structural proteins. Analysis of influenza morphology and ultrastructure can help elucidate viral structure-function relationships as well as aid in therapeutics and vaccine development. While cryo-electron tomography (cryoET) can depict the 3D organization of pleomorphic influenza, the low signal-to-noise ratio inherent to cryoET and extensive viral heterogeneity have precluded detailed characterization of influenza viruses. In this report, we developed a cryoET processing pipeline leveraging convolutional neural networks (CNNs) to characterize the morphological architecture of the A/Puerto Rico/8/34 (H1N1) influenza strain. Our pipeline improved the throughput of cryoET analysis and accurately identified viral components within tomograms. Using this approach, we successfully characterized influenza viral morphology, glycoprotein density, and conduct subtomogram averaging of HA glycoproteins. Application of this processing pipeline can aid in the structural characterization of not only influenza viruses, but other pleomorphic viruses and infected cells. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/472010v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@983f56org.highwire.dtl.DTLVardef@1664734org.highwire.dtl.DTLVardef@1cce73dorg.highwire.dtl.DTLVardef@1617998_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2017

Substrate sequence selectivity of APOBEC3A implicates intra-DNA interactions

The APOBEC3 (A3) family of human cytidine deaminases is renowned for providing a first line of defense against many exogenous and endogenous retroviruses. However, the ability of these proteins to deaminate deoxycytidines in ssDNA makes A3s a double-edged sword. When overexpressed, A3s can mutate endogenous genomic DNA resulting in a variety of cancers. Although the sequence context for mutating DNA varies among A3s, the mechanism for substrate sequence specificity is not well understood. To characterize substrate specificity of A3A, a systematic approach was used to quantify the affinity for substrate as a function of sequence context, length, substrate secondary structure, and pH. We identified the A3A ssDNA binding motif as (T/C)TC(A/G), and found that A3A binds RNA in a sequence specific manner. Furthermore, A3A bound tighter to its substrate binding motif when in a loop compared to linear oligonucleotide. Our results suggest that the A3A affinity and preference for substrate is modulated by the structure of DNA, and not just its chemical identity. Analysis of previously published co-crystal structures of A3A bound to ssDNA in light of the above findings directed the proposal of a new model for the molecular mechanism underlying A3A sequence preference. On a broader scale, the results of this work not only provide key insights into the mechanism of A3s beneficial roles in the cell, especially in viral restriction, but also into A3s deleterious activity such as in the development of cancer.

biochemistry↗