Matthew Tay

Matthew Tay presents an overview of his lab’s research on characterizing coronavirus antigenic landscapes and using mutation analysis and prediction to develop broadly acting antivirals. @idlabs_astar

#Chikungunya: A growing public health crisis😷 With >120,000 cases, 51 deaths in 2023; 46 in #Paraguay. This study used a suite of genomic, phylodynamic, and epidemiologic techniques to characterize the ongoing large chikungunya epidemic in Paraguay.👉doi:10.3201/eid2909.230523

Is it a tall order to do biologic therapeutics discovery, Pk analysis, and meta-analysis of 2000 studies to show its importance in treatment? This is one of the SCI-PHI projects built at @nuspharmacydept by 6 ambitious undergrads - proud to be one of their mentors. #NUSPharmacy

Resonated: “Something that's really tough for people in the USA to really understand is that in Singapore, you can have 40, 50-year plans. So you can really do some amazing things. Whereas in the US, you're always thinking about two-year election cycles.” forbes.com/sites/juergene…

science.org/content/articl… mAbs among the approaches for protecting us against the next pandemic. But can we generate mAbs that protect not just against sarbecoviruses or betacoronaviruses, but also all other coronaviruses? #Coronavirus #SARSCoV2

COVID-19 increased antibody responses against all orrhocoronaviruses, albeit at low levels. How does this affect our protection against additional zoonotic coronaviruses? medrxiv.org/content/10.110… #tayterthoughts #SARSCoV2

ACE2 decoys (but not Spike-directed peptides) are broad neutralizers of SARS-CoV-2. But they may need to be tuned to increase their in vivo efficacy. journals.asm.org/doi/full/10.11… #tayterthoughts #SARSCoV2 #Omicron

229E coronavirus: Spike takes ~8 years to mutate 1% RBD takes 2 years to mutate 1%(journals.plos.org/plospathogens/…) SARS-CoV-2: Spike takes 1 year to mutate 1% RBD takes 4 months to mutate 1% (calculated based on WT, BA2, XBB1.5) SARS-CoV-2 mutates 6-8x faster. #tayterthoughts

Machine learning and language models may be able to predict future SARS-CoV-2 variants. What biological (ACE2 affinity/immune escape parameters) or epidemiological data inputs are required to train good models? pubmed.ncbi.nlm.nih.gov/33446556/ pubmed.ncbi.nlm.nih.gov/35014856/ #tayterthoughts

Memory B cells are selected based on low affinity to antigen, i.e. failure to continue in the germinal center, in order to preserve cross-reactivity to different pathogen variants. pubmed.ncbi.nlm.nih.gov/33125897/ pubmed.ncbi.nlm.nih.gov/27158841/ pubmed.ncbi.nlm.nih.gov/35177475/ #tayterthoughts

I’m #hiring! Looking to do antibody-based therapeutics against infectious disease, including potentially AACs. See our website and contact for details :) antimicrobialbiologicslaboratory.com/contact-us

I wanted to summarize what is known about the new XBB.1.5 variant of SARS-CoV-2, which is starting to generate a lot of interest. (There are no new scientific results in this thread, it simply aggregates previously reported results for those not following topic closely.)