Ashutosh Srivastava

Super excited about this - science with a pint of beer! #circadianclock

Sad. One of the best science magazines. Read and loved almost every article.

Help us celebrate #BiophysicsWeek by contributing a Classical Lay Summary! Your summary will be reviewed by the Early Careers Committee & selected pieces will be featured on the BPS Blog and social media. Submit your piece and a related graphic to eyosebashvili@biophysics.org

@NikoMcCarty This is a beautiful description. Thank you.

A protein moves between its “folded” and “unfolded” forms in less than one-millionth of a second. For a new study, researchers captured this transition for single proteins. The researchers studied eight small proteins, in fact, ranging in size from 35 to 81 amino acids. (An average human protein, for context, is about 400 amino acids.) Each of these proteins has a single domain, and each protein can only exist in one of two states; “unfolded” or “folded.” Because these proteins are so small, they switch between states incredibly fast (like I said, millionths of a second). Coming up with an experiment to measure this switching, especially at the level of individual molecules, seems really, really, really difficult. I mainly decided to read this paper so that I could understand this experiment, and it did not disappoint! First, the researchers purified each protein and put it into a liquid with urea. Urea destabilizes proteins and coaxes them to unfold, so if you place the molecules in *just* the right concentration of urea, then there will be a roughly equal chance the molecule will exist in either its folded or unfolded form. The goal is to find the urea concentration that causes each protein to switch back-and-forth as often as possible. Next, the researchers attached two fluorescent dyes to each protein; one green and one red. These dyes fuse to cysteine amino acids located far apart when the protein is unfolded, but that come closer together when each protein folds. (Importantly, each protein already has many solved structures, so it’s easy to figure out which amino acids are most suitable for the dyes. The dyes are a bit bulky, though, so you need to make sure they don’t disrupt the protein folding.) When the green and red dyes come together, the green dye transfers its energy over to the red instead of emitting its own light. The result is that an unfolded protein appears in roughly equal parts of green and red. But as it transitions into its “folded” state, it emits a larger and larger fraction of solely red photons. But because this folding happens in less than one millionth of a second, and it’s not really possible to see the tiny number of photons emitted by a single protein, the next step was to — somehow — amplify the fluorescent signal emitted from each protein as its folding. Not easy! To solve this problem, the researchers used something called a zero-mode waveguide, which is a tiny sheet of aluminum with holes punched into it. These holes are only about 120 billionths of a meter wide; just enough for a protein to float inside. (Zero-mode waveguides were also used to build the PacBio DNA sequencer.) When a protein drifts into one of these holes, the metal walls concentrate light in a way that makes the dyes glow five to six times brighter than normal. And finally, the researchers used single-photon detectors to measure the signals from each zero-mode waveguide. These are extremely sensitive light sensors that produce an electrical pulse every time a single photon hits them. The sensors record the exact arrival time of each photon with nanosecond precision. They used two of these detectors for each well. A special mirror, called a dichroic beamsplitter, sits in the light path and reflects green light toward one detector while allowing red light to pass through to the other detector. (These sensors are not recording videos. They literally just record the color of photon and the delay from the prior photon. So the dataset looks like this: - 0.000000 ms, green - 0.000003 ms, green - 0.000005 ms, red - 0.000006 ms, green) The researchers used this setup to measure two things: “Waiting time,” which just says how long a protein stays unfolded before it starts to fold; and the “transition path” time, which describes how long the actual crossing from unfolded —> folded takes after it starts. The major takeaway was that smaller proteins have shorter waiting times on average, meaning they move back-and-forth between folded and unfolded states more frequently. (The protein with 35 amino acids had an average waiting time of 42 microseconds, compared to 1.6 seconds for the protein with 81 amino acids.) Surprisingly, though, larger proteins have SHORTER transition times, meaning they transit between the two states faster after the process has begun. The largest protein had a transition time of 0.7 microseconds, compared to 3.1 microseconds for the smallest. TL;DR Evolution has optimized larger proteins to fold more efficiently via cooperativity, where one part of the protein coaxes another part to snap into place. The whole molecule works together, rather than each chain moving independently. I love biophysics <3

@AthiNaganathan @ChemBiochemUMD @CEGLAB_IISERBPR @IndiaDST @iitmadras Congratulations to the entire team 👏

Our latest work is out in PNAS! We show how protein mutations modulate different features of the native ensemble and not just stability. Collaborative work with Fushman group (@ChemBiochemUMD) and Arun @CEGLAB_IISERBPR. Funding from @IndiaDST @iitmadras pnas.org/doi/10.1073/pn…

Join us to shape the future of modern biology @BRIC_CDFD Hyderabad Eager to build an independent, impactful competitive research program? Apply now We offer the best facilities, exciting research environment & competitive funding Where Discovery meets Service

Happy to announce the 8th BioGroupIndia Meeting 3–4 April 2026, BITS Pilani, Pilani Campus, Rajasthan. Founded in 2015 at IIT Kanpur, BioGroup India has grown into an important platform connecting and empowering the Indian life sciences community. biogroupindia.weebly.com

A word of appreciation for @ANRFIndia. The expert comments were promptly shared for rejected grant and now we have tangible inputs as to how we can improve our application. Also, considering the expert comments were quite positive, we are more confident going further.

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Applications open for ICTP-IISc workshop on Physics of Cancer (20 experimental and/or computational speakers in stochastic cellular decisions, cellular competition & cooperation, soft matter aspects and tumor-immune co-evolution dynamics). Apply by Feb 15! indico.ictp.it/event/11123/ov…

@StructBioinfo @BiophysicalSoc Congratulations, Raghu.

Starting the year with a bang! Selected as the Indian Ambassador for @BiophysicalSoc 's seventh cohort (2026-2028)!!! Eagerly looking forward to working with other ambassadors to promote biophysics and bioinfo in India. 🥳🙌 biophysics.cld.bz/Biophysical-So…

Applications open for our six-week computational oncology summer training 2026 (May 18 - June 26; due: Feb 15, 2026). tinyurl.com/bdhth4em Plz RT @biopatrika @BE_IISc @iiscbangalore @rakeshthejoy @karthikraman @abandopa @DynamicsLiving @mathoncbro @DeepakNModi @r_sabarinathan

Manuscript alert ! Excited to launch NAViFluX, a revolutionary tool for metabolic network visualization, analysis & refinement ! Mix-n-match your own layouts to prioritize hypotheses. Congrats @hegade_BK @PSHarish27 on this great achievement! #SystemsBiology #Bioinformatics

Really excited to host two incredible researchers in the field of Chronobiology at @iitgn today. We will be discussing circadian rhythms across scales and organisms. Please drop by if you are in and around Gandhinagar.

@savoirefaire85 @BiophysJ @iitgncompbio @Karthick_Sudars Thanks to @DBTIndia for Ramalingaswami Re-entry Fellowship and International Collaborative Research Program of Institute for Protein Research, Osaka University for financial support

Excited to share our recent paper in collaboration with @savoirefaire85 from Osaka University, in @BiophysJ. Here, we explore the domain coupled dynamics of bHLH-PAS domain transcription factors. This was led by @iitgncompbio PhD student @Karthick_Sudars authors.elsevier.com/a/1m5qG1SPTBhk-

@gsneha261 @techreview @AmyNordrum @euanashley Congratulations Sneha. Well deserved 👏

Honored to be named Innovator of the Year and included in the Innovators Under 35 cohort by @techreview (special shoutout to @AmyNordrum). Huge thanks to @euanashley and the ultra-rapid sequencing team—your vision and drive made this possible. Really grateful to all my mentors, teachers, friends and family who have always supported me. Excited to continue pushing the boundaries of what’s possible at my current home in @EPrinceton @Princeton.🚀 ter.li/85murk

Two members of the @iitgncompbio group graduated with M. Tech in Biological Engineering degree at the recently held 14th Convocation of @iitgn. Extremely proud of both Vishnu and Rahul. Congratulations 🎊 👏

We looking for students with an Engineering background to help design and develop an experimental arena to automate quantification of a fly behavior. See attached for more details. Please help spread the word.

We have started the screening of applications for this position and also extended the deadline to 25th May, 2025. Please apply if interested . Details here- drive.google.com/file/d/1XpqnKy… Apply here- forms.office.com/r/bm5MZs6wmy