Luke Lambourne

[Gökhan Hotamışlıgil @ghotamis]

Excited to share our latest paper led by Renata Goncalves @RenataG81952725: CoQ imbalance drives reverse electron transport to disrupt liver metabolism.

https://t.co/svgsVGKCfd

We uncover how altered CoQ redox balance triggers RET and rewires hepatic metabolism to offer critical insights into a decades old question. Meticulously mapping each one of the 11 sites of the mitochondrial electron transport chain in the liver showed site IQ as the sole source of excess mitochondrial ROS, produced via reverse electron transport. This defect is driven by CoQ imbalance in obesity, disrupts glucose metabolism.

These findings may have implications for many diseases and open up new treatment possibilities where broad antioxidants have failed to generate therapeutic benefit. Our findings may also offer a potential mechanism and solution for the increased diabetes risk seen in a small fraction of statin users.

Huge congratulations to Renata Goncalves @RenataG81952725 for leading this work and for her immense dedication and patience to bring it to a conclusion. Congratulations to all contributors from the @hotamisligil lab and our amazing collaborators Isabel Graupera @igraupe and Shawn Burgess @Isotopomer

Curious? The 93-page-long peer review file is full of useful information and insightful discussions.

[Renata Goncalves @RenataG81952725]

Thrilled to share that our latest study is now published in @Nature!
Grateful to our amazing collaborators at @gshlab and @MET_HSPH.

https://t.co/hknvlAj6Dv

https://t.co/OUwnI6rLV8

[Renata Goncalves @RenataG81952725]

More insights from our study published today in @Nature: We uncover how mitochondrial dysfunction in the liver contributed to drive insulin resistance in obesity. Read the @HarvardChanSPH press release 👉 https://t.co/iL9vDTajcp

[Jeffrey Flier @jflier]

Using idc rates to optimize research deserves study and modification. But the approach just taken was designed not to improve the process, but to harm institutions, researchers and biomed research. Many supporting this action seem ignorant about the US biomed research ecosystem.

[Mikko Taipale @mike_tilapia]

Our latest paper is out! In collaboration with @DrAnneCarpenter, we conducted a systematic high-content screen to understand the role of protein mislocalization in diverse human disorders. 1/ https://t.co/pQzVx0hOrC

[Luke Lambourne @LukeLambs]

@simongerman600 Not exactly that one but Boston has the Mapparium which is an inverted globe

https://t.co/pjlKBec7v2

[Jason Sheltzer @JSheltzer]

Let’s play a little game.

Let’s say that you’re the CSO at a cancer pharma company, and you have to choose a target to go after.

Here’s a gene – high expression is associated with poor prognosis in brain cancer. Looks like a good candidate for an inhibitor right?

[Luke Lambourne @LukeLambs]

@gangxue0502 Thank you! We just wrote our own python functions to visualize the splice forms. The problem with all the existing solutions was that we were only interested in the protein coding regions for our study. All the code is here: https://t.co/yU5JNeUwEx

[Luke Lambourne @LukeLambs]

I'm excited to share our preprint on the molecular properties of transcription factor protein isoforms:
https://t.co/RWGTPeyQ4Z

[Michael Baym @baym]

Prospective power analysis is hilarious because your replace an arbitrary guess of sample size with an arbitrary guess of the effect size you’ve yet to measure, do a touch of arithmetic, and suddenly it’s considered rigorous

[Mikko Taipale @mike_tilapia]

Our latest work on developing a potent and specific tool for activating or repressing endogenous splicing events is out! https://t.co/qHn6LEVsMC

[Oleg Kovalevskiy @OVKovalevskiy]

@jankosinski @GoogleDeepMind Thank you Jan for the intensive testing and interesting findings! For the templates, it is the same cutoff as mentioned in the paper, i.e. 2021-09-30. We will add this to the Server FAQ for clarity and will let users know if we change this date

[Gunes Parlakgul @gparlakgul]

https://t.co/ViqfP1CzzO
Happy to share our latest work on hepatic ER and mitochondria structure. We analyzed ER & mitochondria shape and their interactions across liver zonation, in fasting/feeding cycles and in obesity!
Grateful for everyone involved! @apsarruda @ghotamis Shan & Song @refikanadol @BerkeleyMetBio @UCBerkeley @NatureAtCal @Harvard @HHMIJanelia @Yale

[Dr. Kaia Mattioli @kaia_mattioli]

excited to share the first story from my postdoc today!! we profiled hundreds of transcription factor (TF) isoforms & found that two-thirds of alternative TF isos differ from their cognate reference iso in at least 1 key molecular activity

https://t.co/VvMjAoMhef

[Luke Lambourne @LukeLambs]

Preprint: https://t.co/RWGTPeyQ4Z
Website to browse the data: https://t.co/FkESfqDN0T

Thanks coauthors @kaia_mattioli @fuxmanlab @nsalomonis @macalderwood @annaabananabell and lots not on twitter!

[Luke Lambourne @LukeLambs]

Alternative TF isoforms often had different localization and condensate formation properties from the corresponding reference isoform

[Luke Lambourne @LukeLambs]

Based on these widespread differences in molecular functions, alternative isoforms of TFs form a crucial, but neglected, layer in the regulation of gene expression. Improving knowledge of this layer will be key to future progress in understanding cellular function and dysfunction

[Luke Lambourne @LukeLambs]

And, once you account for sequence identity, isoforms of the same gene are as different as paralogous genes

[Luke Lambourne @LukeLambs]

Changes in binding to cofactors and signaling proteins were associated with changes in activation

[Luke Lambourne @LukeLambs]

Of all protein-partners, it was the obligate dimerizing of TFs that was most preserved across different isoforms (e.g. bHLH-bHLH, bZIP-bZIP etc.) suggesting a need to preserve those for these alternative isoforms to function

[Luke Lambourne @LukeLambs]

We found most alternative isoforms differed from the reference isoform of the same gene. Those differences are really challenging to predict from sequence features, e.g. differences in disordered regions far from the DNA-binding domain frequently affected DNA-binding