Maslov lab

We have been awarded a UIUC Strategic Research Initiative (SRI) program with the proposal “Multi-scale learning for analysis of spatial transcriptomics data” .

Our team will start working on April 2, 2024:

• Sergei Maslov (PI), Department of Bioengineering and Department of Physics (GCOE)
• Olgica Milenkovic (co-PI), Department of Electrical and Computer Engineering (GCOE)
• Maxim Raginsky (co-PI), Department of Electrical and Computer Engineering (GCOE)
• Ilan Shomorony (co-PI), Department of Electrical and Computer Engineering (GCOE)
• Hanghang Tong (co-PI), Department of Computer Science (GCOE)
• Hee-Sun Han (co-PI), Department of Chemistry (LAS)
• Michael Robben (co-PI), Department of Animal Sciences (ACES)
• Dave Zhao (co-PI), Department of Statistics (LAS)
• Alvaro Hernandez (Senior Personnel, Experimental Support), Roy J. Carver Biotechnology Center

Sergei and Zihan attended the APS March meeting in Minneapolis and gave talks on recent work on microbial communities. It was also a chance to meet with lab alumni: Tong Wang and Akshit Goyal. We also made contacts and discussed potential collaborations with several experimental groups. Griffin Chure from Jonas Cremer’s group at Stanford will give a talk at our group meeting on 3/29 at 9:30am CT.

Sergei + Alexei Tkachenko’s paper on origin of life has been accepted at eLife:
https://elifesciences.org/reviewed-preprints/91397/reviews
We gave an interview for IGB press release, which will be coming up shortly.

Tarun +Sergei submitted a paper on a model of a complex synthetic human gut microbiome: Coarse-Grained Model of Serial Dilution Dynamics in Synthetic Human Gut Microbiome.   The model is necessarily coarse-grained because the community has >60 species! Data for serial dilution experiments are from a paper co-authored by a former group member, Veronika Dubinkina.

 

See UIUC Physics Department press release and The Atlantic magazine article.  In (eLife 2021) we developed a new epidemiological model that encompasses randomness and dynamic variability of individual social interactions and used it to explain COVID-19 waves in US between July 2020 and March 2021.

Our eLife research editor was Mark Lipsitch, Harvard epidemiologist and the director of science in the newly formed Disease Forecasting Center at CDC. In his editorial statement, he wrote: “This is an excellent and elegant example of what theory can do at its best in epidemiology: it takes a widely observed phenomenon that is an ‘”embarrassment’” (my word) to current theories; proposes a parsimonious explanation that is plausible for the phenomenon by extending the existing theories in a specific way; and makes a plausible case for the importance of the mechanism in explaining key features of the data. In this case, the embarrassing phenomenon is long periods of very slowly changing incidence/prevalence, and the modification to theory is incorporation of dynamic social heterogeneity. This should stimulate much further work in the field. Congratulations to the authors.”

See IGB press release.

We studied population dynamics (Nat Comm 2021 Nov) in a community of microbes sequentially utilizing resources (diauxie) in the order determined by each species regulatory network. Such communities realized both in serial dilution experiments, as well as in naturally occurring boom-and-bust cycles (e.g., in the upper ocean microbiome of temperate regions).

In a ceremony attended by Gov. J.B. Pritzker, Sergei Maslov was among 30 key leaders of the University of Illinois COVID-19 response team honored with the Presidential Medallion. This medallion is the highest honor that the U of I  system president can bestow. Among others, it was previously awarded to Arthur Clarke, Thomas M. Siebel, and David W. Grainger.

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Our new paper was just published as a direct submission in PNAS and covered in this press release.  Here we introduce the concept of  “transient collective immunity” and argue that it described COVID-19 epidemics better than a more familiar concept of “herd immunity”. The main difference between these two concepts is that transient collective immunity is not expected to last forever. This is similar to the transient nature of biological immunity caused by decreasing antibody counts and the emergence of new variants. However, in our case, this “expiration date” is caused entirely by changes in levels of individual social activity.