David Bernstein

Postdoc at UC Berkeley @AdamArkinLab. PhD from Boston U @segrelab. Alum of @uvmcems. Systems biology, microbial communities, and metabolic networks.

[David Bernstein @d_b_bernstein]

Very excited to have this review out! We cover major sources of uncertainty in genome-scale metabolic modeling and approaches developed for addressing this uncertainty. We hope this review will serve as a roadmap for those interested in further developing methods in this area!

[Daniel Segrè @dsegre]

Addressing uncertainty in genome-scale metabolic model reconstruction and analysis, @GenomeBiology https://t.co/dbNpN7Co26 by @d_b_bernstein, @SnorreSulheim, @AlmaasLab

[Alan Pacheco @alanrpacheco]

Every day, we learn more and more about how microbes interact with each other and with their hosts.

How can we ensure we’re making the most out of this growing wealth of data?

1/12

[Vivek Mutalik @vivek_mutalik]

We are looking for a postdoc who ❤️phages & is passionate about uncovering host-phage specificity determinants by generating >200K phage-bacteria interactions, 1000’s of HT genetic assays & powerful machine learning algorithms. Work will be in my lab & @AdamArkinLab plz reach out

[AdamArkin_Lab @AdamArkinLab]

Another great contribution to improving annotation and understanding metabolism of microbes by my long term collaborator Morgan Price! https://t.co/GMvPQ8367W

[AdamArkin_Lab @AdamArkinLab]

Hey All,
We have a great postdoctoral position to apply the awesome power of the one of the most powerful supercomputers on earth to build data-driven and mechanistic approaches to model large metagenomic compendia. https://t.co/VB9VQTQjta

[Josh Goldford @joshuagoldford]

Are two coenzymes better than one? Find out what selective pressures might have driven the usage of multiple redundant coenzymes in modern metabolism in our latest paper, published today in @PNASNews! 1/2

https://t.co/2gAu2k179O

[Alan Pacheco @alanrpacheco]

We also compiled a broad set of resources that researchers with varying levels of computational/experimental expertise can use to get started with using models for microbiome studies:

https://t.co/aw0LjnpGg3

[Maureen Carey @MaureenACarey]

Check out the results of our survey & publication in @mSystemsJ:

Enhancing Microbiome Research through Genome-Scale Metabolic Modeling https://t.co/E5IQp6quCG

@symbiosisnana @d_b_bernstein @Mbiggs86153124 @MicroMindy @beagj @MeiyappanL @alanrpacheco @SnorreSulheim @medlockgreg

[segrelab_news @segrelab]

Our comprehensive guide to #COMETS (Computation Of Microbial Ecosystems in Time and Space) is out at @NatureProtocols. Read at https://t.co/B56rp7DRXA. We hope you will find it useful for #modeling the dynamics of #metabolism in microbial communities. #dFBA #microbiomes. 1/6

[Devlin Moyer @devmoy1]

My first paper on grad school work has just been published; ironically it has almost nothing to do with my thesis project https://t.co/oESww49XnR

[Daniel Segrè @dsegre]

Analyzing reaction networks in artificial string chemistries (e.g. ab+aa->abaa) helps understand the evolution of metabolism. @devmoy1 w @d_b_bernstein & @alanrpacheco, developed a toolbox (https://t.co/fQ46nhUbdC) to do #FBA of string chemistries @JMolEvo https://t.co/LBYlwbqwOj

[David Bernstein @d_b_bernstein]

@SnorreSulheim @AlmaasLab

[johannes zimmermann @_jozimmermann]

Inspiring and important read on the sources of uncertainty in metabolic modeling by David Bernstein et al from the Segre lab @dsegre https://t.co/yDv7vcRGO9

[Alan Pacheco @alanrpacheco]

We know that the resources available to a microbial community play a big role in shaping its structure and function.

So if we wanted to design a community with specific properties, could we find a combination of nutrients that would get us there? (1/5)

https://t.co/PzcJ7aHew5

[Alan Pacheco @alanrpacheco]

How does resource diversity shape microbial communities?

In our new paper, @MelisaLKO, @dsegre, and I identify key factors that define this relationship and quantify how communities challenge expectations of growth and diversity in complex environments.

https://t.co/qL4xqIIvFr

[Maureen Carey @MaureenACarey]

Do you like the #microbiome?

Do you like metabolic models?

If yes to EITHER of these questions, share your perspective on the use of metabolic modeling in the microbiome field!
https://t.co/lmBV9eFXRd

[COMETS @RunCOMETS]

It's happening! https://t.co/sEG0pdJZwg

[Eivind Almaas 🦋@a1maas.bsky.social @AlmaasLab]

Genome-scale metabolic models (GEMs) aim to capture a representation of the entirety of metabolic functions of a cell. We review their major sources of uncertainty and survey existing approaches developed for representing and addressing them. @segrelab
https://t.co/MuwvdfOqgO

[David Bernstein @d_b_bernstein]

Introducing the BioMe plate! This modified 96-well microplate enables the observation of microbes interacting across a porous membrane. Very happy to have the paper from my graduate work with @segrelab co-led by Charles Jo (who also made this awesome GIF) out on BioRxiv now!

[bioRxiv @biorxivpreprint]

A co-culture microplate for real-time measurement of microbial interactions https://t.co/3nDoHGjV4L #bioRxiv

[Alan Pacheco @alanrpacheco]

Announcing the latest preprint from my PhD work! Here, we show how specific microbial community behaviors can be identified via rational environmental modification. 1/3 https://t.co/eYlC0PssVs

[KBase @DOEKBase]

Today's #FFF: researcher's using #KBase have been quantifying metabolic networks between microbes in the human oral microbiome.
Check it out here: https://t.co/KYohr9JRKG.