Single Molecule Microbiology

We’ve updated the research page to include updates on new preprints frkom our lab and in collaboration with other labs. Congrats to João and Ruilan for their work on the new preprint: Mycobacterium tuberculosis FtsB and PerM interact via a C-terminal helix in FtsB to modulate cell division. Congrats to lab alumnus Sara Costa as well for her paper from Mariana Pinho’s lab published last month: The role of GpsB in Staphylococcus aureus cell morphogenesis

We’ve also got two preprints out on SARS-CoV-2 related topics. First, with Florence Débarre, we found that stories about deleted viral sequences from June 2021 were not at all consistent with data available at the time. Read about it in the preprint: A critical reexamination of recovered SARS-CoV-2 sequencing data. We also published a very short preprint regarding the surprising observation that mutation rates in SARS-CoV-2 during the pandemic are strongly correlated with RNA basepairing. It will be interesting to see how this can be incorporated into models predicting the impact of mutations. Read the preprint here: Secondary structure of the SARS-CoV-2 genome is predictive of nucleotide substitution frequency.

Work led by Liv Zimmermann and Petr Chlanda was recently published in Nature Communications: SARS-CoV-2 nsp3 and nsp4 are minimal constituents of a pore spanning replication organelle. The work used cryo-electron tomography to find that cells expressing only SARS2 non-structural proteins nsp3 and nsp4 produced hexameric pores decorating double-membrane vesicles (DMV). Previously, expression of IBV nsp4 alone was found to induce membrane pairing and nsp6 was considered to be a likely possible constituent of DMV pores in MHV- and SARS2-infected cells.

Our lab’s contribution to the paper incorporated results from our preprint that was the first report of the Predicted binding interface between coronavirus nsp3 and nsp4 which has yet to be confirmed experimentally, yet is consistent with a mutations known to disrupt nsp4 and sequence conservation during the SARS2 pandemic. Predicted structures and molecular dynamics helped interpret Cryo-ET data that lacked resolution in the DMV lumen compared to the hexameric nsp3 crown of the DMV pore.

Congratulations to Sara Costa, who defended her thesis and was awarded her PhD today. In Sara’s thesis, New approaches to study Staphlococcus aureus elongation and division, she discusses work implementing fluorescence microscopy techniques for studying protein-protein interaction in S. aureus and reports identifying GpsB as a non-essential protein that impacts cell elongation in S. aureus – this work is preprinted at biorxiv and was overseen by Sara’s co-supervisor, Mariana Pinho.

This only scratches the surface of the work covered during Sara’s PhD. She also played an essential role in our investigation of the E. coli divisome and in single-molecule imaging of transcription elongation in E. coli.

A new preprint on environmental sampling has been published. Crits-Cristoph and colleagues describe how metatranscriptomics data can be used to identify animals and animal viruses in Huanan Seafood Wholesale Market at the beginning of the COVID-19 pandemic. Zach helped analyze statistical correlations in the data, demonstrating Carr et al’s claim that it can be difficult, if not impossible, to infer direct association of abudandance from statistical association. The supplemental figure here shows that combining samples from two different days, with two different sampling strategies, can transform a lack of correlation into an apparent, unrealistically strong correlation. Co-corresponding author Florence Débarre noted that this is a demonstration of Simpson’s Paradox.

Zach first applied an early version of this analysis to another data set to examine what drives apparent positive and negative correlation between nucleic acid abundance in environmental sequencing. As he discussed for an article, the appearance of unrealistic correlation between species that aren’t susceptible to SARS-CoV-2 and viral RNA is not a reason to dismiss this data entirely. Rather, correlation in the data set largely arises from clear artifacts of combining samples from different days with different sampling strategies. This is the largest, but not the only artifact impacting this data. As discussed by Saccenti et al, correlated, multiplicative error also plays a role in addition to nucleic acid degradation over time and so on.

Perhaps we can move beyond assigning blame for the pandemic to learning from it to reduce the likelihood of the next one. This paper analyzes data from the epicenter of the COVID-19 pandemic and identifies additional risks posed by the wildlife industry there that could be considered by countries drafting the WHO Pandemic prevention, preparedness and response accord. An equivalent of what happened at the end of 2019 could have happened, and still could happen again, in many places in the world and with many different pathogens, so it’s worth thinking about realistic, low-cost ways to reduce the likelihood that this happens.

We aspire to keep this updated from this point forward and are looking ahead to sharing our ongoing work soon.