Steph N. Seifert, PhD's Avatar

Steph N. Seifert, PhD

@stephseifertphd.bsky.social

PI of the Molecular Ecology of Zoonotic and Animal Pathogens Lab Co-PI, Viral Emergence Research Institute Interested in virology, evolution, ecology, and still cares about diversity and equity in STEM she/her

1,689 Followers  |  403 Following  |  40 Posts  |  Joined: 15.10.2023  |  1.7337

Latest posts by stephseifertphd.bsky.social on Bluesky

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In this Perspective, Ryan Langlois hypothesizes that antiviral genes are evolutionarily selected for their function at fever temperatures yet are commonly studied at basal temperatures, a potential blind spot in our understanding of antiviral gene mechanisms. rupress.org/jem/article/...
#Virology

11.12.2025 18:20 β€” πŸ‘ 12    πŸ” 8    πŸ’¬ 1    πŸ“Œ 0

You can do this right now:

Think of a person who wrote a paper you love, whose work influenced or helped you, or has made your professional life better.

Search up their email address. Shoot them a quick email of thanks. It means so, so much. This is a rough time of year, share some joy.

11.12.2025 22:08 β€” πŸ‘ 560    πŸ” 207    πŸ’¬ 11    πŸ“Œ 31
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NIH shut out hundreds of young scientists from funding to start their own labs Special Report: The NIH has shut out hundreds of young scientists from funding to start their own labs.

"The only reason I don’t have this funding is because my last name is Rodriguez,” he said. β€œIt has nothing to do with the science."

STAT on the betrayal of early-career researchers:
www.statnews.com/2025/12/08/t...

08.12.2025 11:43 β€” πŸ‘ 89    πŸ” 60    πŸ’¬ 1    πŸ“Œ 2
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Paramyxoviruses in Old World fruit bats (Pteropodidae): An open database and synthesis of sampling effort, viral positivity, and coevolution Author summary Paramyxoviruses are a family of viruses that include the human measles and mumps viruses as well as emerging zoonoses like Hendra and Nipah henipaviruses. These henipaviruses spill over...

We created a database of all published paramyxovirus detection attempts in pteropodid bats! Lots of sampling gaps and avenues for future study ⬇️ Excited to share this PhD chapter with @danjbecker.bsky.social and @viralemergence.org, out last month in @plos.org πŸ¦‡πŸ¦ πŸ”“

journals.plos.org/plosntds/art...

02.12.2025 12:38 β€” πŸ‘ 9    πŸ” 4    πŸ’¬ 0    πŸ“Œ 0
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Applied to COVID-19 in California, the approach yields more accurate and more stable short-term forecasts than RNNs, LSTMs, GRUs, Transformers, and naΓ―ve baselines.

πŸ”— royalsocietypublishing.org/doi/10.1098/...

01.12.2025 12:31 β€” πŸ‘ 3    πŸ” 3    πŸ’¬ 0    πŸ“Œ 0
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Species-observer link and kernel density estimation of background points allow for sampling bias correction in bird species distribution models vist.ly/4gc4n #Birds #SDM #SamplingBias

28.11.2025 09:24 β€” πŸ‘ 8    πŸ” 4    πŸ’¬ 0    πŸ“Œ 0
Graphic representation of the recombination events in the Sugarlandvirus I and J variants. Top left: Representation of the variants isolates in the different strains in the three lines. Genome fragments of each parent are represented in a different color. Regions with the most abundant recombination events are marked and associated with a schematic representation of the functional annotation and intergenomic similarity between the two parental phages. Bottom left: 3D folding of the RBPγ. The consensus recombinant region, which is associated with the infection of the K-type 47, is represented in light orange. Variable positions detected in the protein sequence alignment of the variants are represented as hot pink spheres. The table indicates the percentage of identity of the parental protein sequences in three protein regions limited by the amino acids indicated. Right: Transmission electron microscopy (TEM) image of Klebsiella myoviruses artificially coloured, showing their characteristic contractile tails and icosahedral capsids. Image acquired by the Environmental and Biomedical Virology group (Institute for Integrative Systems Biology, Universitat de València-CSIC).

Graphic representation of the recombination events in the Sugarlandvirus I and J variants. Top left: Representation of the variants isolates in the different strains in the three lines. Genome fragments of each parent are represented in a different color. Regions with the most abundant recombination events are marked and associated with a schematic representation of the functional annotation and intergenomic similarity between the two parental phages. Bottom left: 3D folding of the RBPγ. The consensus recombinant region, which is associated with the infection of the K-type 47, is represented in light orange. Variable positions detected in the protein sequence alignment of the variants are represented as hot pink spheres. The table indicates the percentage of identity of the parental protein sequences in three protein regions limited by the amino acids indicated. Right: Transmission electron microscopy (TEM) image of Klebsiella myoviruses artificially coloured, showing their characteristic contractile tails and icosahedral capsids. Image acquired by the Environmental and Biomedical Virology group (Institute for Integrative Systems Biology, Universitat de València-CSIC).

Capsule diversity limits #phage host range by affecting receptor-binding protein (RBP) interactions in capsulated #bacteria. @pilardomingoc.bsky.social &co show that generalist phages evolve host range via RBP mutation & recombination, but specialists remain stable @plosbiology.org πŸ§ͺ plos.io/48nvOqY

28.11.2025 13:58 β€” πŸ‘ 11    πŸ” 7    πŸ’¬ 1    πŸ“Œ 0
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What makes bird flu spill over to humans? 4y funded PhD in the genomics and molecular virology behind zoonosis of avian influenza A virus, working with @tompeacock.bsky.social and others between Liverpool, Pirbright, and Uppsala!

open to applications until next week!

28.11.2025 14:34 β€” πŸ‘ 11    πŸ” 5    πŸ’¬ 2    πŸ“Œ 0
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plinkQC: An Integrated Tool for Ancestry Inference, Sample Selection, and Quality Control in Population Genetics www.biorxiv.org/content/10.1... 🧬πŸ–₯️πŸ§ͺ R package meyer-lab-cshl.github.io/plinkQC/ #Rstats

28.11.2025 15:01 β€” πŸ‘ 14    πŸ” 10    πŸ’¬ 0    πŸ“Œ 0
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Ecology and spread of the North American H5N1 epizootic - Nature The panzootic of highly pathogenic H5N1 since 2021 was driven by around nine introductions into the Atlantic and Pacific flyways, followed by rapid dissemination through wild migratory birds, primaril...

Our lab's paper describing the North American H5N1 epizootic is out now in Nature! So thrilled to have this out, and congratulations to @lambod50.bsky.social for all the fantastic work on this: www.nature.com/articles/s41...

12.11.2025 19:33 β€” πŸ‘ 138    πŸ” 65    πŸ’¬ 6    πŸ“Œ 7
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Viral diversity and zoonotic risk in endangered species A growing body of evidence links zoonotic disease risk, including pandemic threats, to biodiversity loss and other upstream anthropogenic impacts on ecosystem health. However, there is little current...

NEW! 🦠🦧 We revisited a perplexing paradox: do wildlife really pose less of a risk to human health as they become more endangered? Turns out, it's sampling bias all the way down: conservation risks correlate with disease surveillance blindspots. πŸ”“ esajournals.onlinelibrary.wiley.com/doi/full/10....

25.11.2025 13:25 β€” πŸ‘ 1360    πŸ” 244    πŸ’¬ 20    πŸ“Œ 12
Model is:

b3 <- scasm(
  y ~ s(x0, bs = "bs", k= k) + s(x1, bs = "sc", xt = "m+", k = k) +
         s(x2, bs = "bs", k = k) + s(x3, bs = "bs", k = k),
  family=poisson, bs=200
)

The second smooth `s(x1) is a shape constrained smooth with a positive monotonicity constraint (xt = "m+").

The `bs = 200` arguments uses 200 boostrap samples, which generates bootstrap distributions for each coefficient in the model. These bootstrap samples respect the shape constraints, while the usual +/- 2 SE credible intervals may not.

The uncertainty in the partial effects is shown by two credible interval bands; a dark blue central band is a 68% Bayesian credible interval, while the lighter blue outer interval is a 95% Bayesian credible interval.

The background of each panel is light grey with white grid lines, in a similar style to ggplot2's default theme.

Model is: b3 <- scasm( y ~ s(x0, bs = "bs", k= k) + s(x1, bs = "sc", xt = "m+", k = k) + s(x2, bs = "bs", k = k) + s(x3, bs = "bs", k = k), family=poisson, bs=200 ) The second smooth `s(x1) is a shape constrained smooth with a positive monotonicity constraint (xt = "m+"). The `bs = 200` arguments uses 200 boostrap samples, which generates bootstrap distributions for each coefficient in the model. These bootstrap samples respect the shape constraints, while the usual +/- 2 SE credible intervals may not. The uncertainty in the partial effects is shown by two credible interval bands; a dark blue central band is a 68% Bayesian credible interval, while the lighter blue outer interval is a 95% Bayesian credible interval. The background of each panel is light grey with white grid lines, in a similar style to ggplot2's default theme.

A new release of the mgcv #RStats πŸ“¦ is out on CRAN and Simon Wood (U Edinburgh) has added some significant new features despite the small bump in version number:

🌟 scasm() for estimating GAMs with shape constrained smooths. Can be used with any family & smoothness selection is via the EFS method

12.11.2025 11:28 β€” πŸ‘ 95    πŸ” 24    πŸ’¬ 3    πŸ“Œ 5

PSA for people with NIH grant periods starting January 1st (including most NIGMS MIRAs): your RPPR is due Saturday, but they haven’t sent out the usual automated reminders, presumably due to the shutdown

11.11.2025 01:20 β€” πŸ‘ 93    πŸ” 83    πŸ’¬ 0    πŸ“Œ 3
Prenylated human ZAP and mammalian KHNYN can independently restrict naturally CpG-enriched ROSV. Top: CpG content of retroviruses (ROSV in black, ROSV-mCherry reporter virus in pink dashed line, MLV in orange, and HIV-1 in blue) calculated as # CpG per 100 nucleotides over a sliding window (graph). Schematic of retrovirus open reading frame (ORF) organization (top). Bottom left: Retroviral assembly and single-cycle infectivity results of human ZAP-L, ZAP-S, and mutants effects on ROSV showing relative percent ROSV infected cells (% mCherry-positive; % mCh+) as determined by flow cytometry. DF-1 cells transfected with increasing plasmid amounts of indicated host proteins (100, 200, or 400 ng), 1,500 ng ROSV, and 200 ng VSV-G. Infectivity is relative to backbone pcDNA3.2 transfections (Mock). Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, ZAP proteins, and ACTIN loading controls from cellular lysates. Bottom right: Retroviral assembly and single-cycle infectivity results of human KHNYN, mutants, and mammalian KHNYN homologs (from pig, dog, and platypus) on ROSV infectivity. Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, human KHNYN proteins, and ACTIN loading controls from cellular lysates. Note mammalian KHNYN orthologues were not detected by human KHNYN antibodies.

Prenylated human ZAP and mammalian KHNYN can independently restrict naturally CpG-enriched ROSV. Top: CpG content of retroviruses (ROSV in black, ROSV-mCherry reporter virus in pink dashed line, MLV in orange, and HIV-1 in blue) calculated as # CpG per 100 nucleotides over a sliding window (graph). Schematic of retrovirus open reading frame (ORF) organization (top). Bottom left: Retroviral assembly and single-cycle infectivity results of human ZAP-L, ZAP-S, and mutants effects on ROSV showing relative percent ROSV infected cells (% mCherry-positive; % mCh+) as determined by flow cytometry. DF-1 cells transfected with increasing plasmid amounts of indicated host proteins (100, 200, or 400 ng), 1,500 ng ROSV, and 200 ng VSV-G. Infectivity is relative to backbone pcDNA3.2 transfections (Mock). Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, ZAP proteins, and ACTIN loading controls from cellular lysates. Bottom right: Retroviral assembly and single-cycle infectivity results of human KHNYN, mutants, and mammalian KHNYN homologs (from pig, dog, and platypus) on ROSV infectivity. Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, human KHNYN proteins, and ACTIN loading controls from cellular lysates. Note mammalian KHNYN orthologues were not detected by human KHNYN antibodies.

What are the #antiviral barriers to cross-species transmission of #zoonotic #influenza A viruses? @jordanbeckerphd.bsky.social @langloislab.bsky.social &co show that CpG-enriched avian #viruses are restricted by several mammalian proteins, including ZAP & KHNYN @plosbiology.org πŸ§ͺ plos.io/47fkMVp

29.10.2025 17:31 β€” πŸ‘ 9    πŸ” 3    πŸ’¬ 0    πŸ“Œ 0
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I'm v excited to be recruiting a PhD student to work on badger behaviour and ecology! Starting date is March 2026; see the ad here, or message me for more details: www.gregalbery.me/s/March-2026...

03.10.2025 14:05 β€” πŸ‘ 57    πŸ” 64    πŸ’¬ 0    πŸ“Œ 1
Prenylated human ZAP and mammalian KHNYN can independently restrict naturally CpG-enriched ROSV. Top: CpG content of retroviruses (ROSV in black, ROSV-mCherry reporter virus in pink dashed line, MLV in orange, and HIV-1 in blue) calculated as # CpG per 100 nucleotides over a sliding window (graph). Schematic of retrovirus open reading frame (ORF) organization (top). Bottom left: Retroviral assembly and single-cycle infectivity results of human ZAP-L, ZAP-S, and mutants effects on ROSV showing relative percent ROSV infected cells (% mCherry-positive; % mCh+) as determined by flow cytometry. DF-1 cells transfected with increasing plasmid amounts of indicated host proteins (100, 200, or 400 ng), 1,500 ng ROSV, and 200 ng VSV-G. Infectivity is relative to backbone pcDNA3.2 transfections (Mock). Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, ZAP proteins, and ACTIN loading controls from cellular lysates. Bottom right: Retroviral assembly and single-cycle infectivity results of human KHNYN, mutants, and mammalian KHNYN homologs (from pig, dog, and platypus) on ROSV infectivity. Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, human KHNYN proteins, and ACTIN loading controls from cellular lysates. Note mammalian KHNYN orthologues were not detected by human KHNYN antibodies.

Prenylated human ZAP and mammalian KHNYN can independently restrict naturally CpG-enriched ROSV. Top: CpG content of retroviruses (ROSV in black, ROSV-mCherry reporter virus in pink dashed line, MLV in orange, and HIV-1 in blue) calculated as # CpG per 100 nucleotides over a sliding window (graph). Schematic of retrovirus open reading frame (ORF) organization (top). Bottom left: Retroviral assembly and single-cycle infectivity results of human ZAP-L, ZAP-S, and mutants effects on ROSV showing relative percent ROSV infected cells (% mCherry-positive; % mCh+) as determined by flow cytometry. DF-1 cells transfected with increasing plasmid amounts of indicated host proteins (100, 200, or 400 ng), 1,500 ng ROSV, and 200 ng VSV-G. Infectivity is relative to backbone pcDNA3.2 transfections (Mock). Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, ZAP proteins, and ACTIN loading controls from cellular lysates. Bottom right: Retroviral assembly and single-cycle infectivity results of human KHNYN, mutants, and mammalian KHNYN homologs (from pig, dog, and platypus) on ROSV infectivity. Below, western blots detecting ROSV cleaved Gagp19 in supernatant virions as well as full-length ROSV GagPr76, human KHNYN proteins, and ACTIN loading controls from cellular lysates. Note mammalian KHNYN orthologues were not detected by human KHNYN antibodies.

What are the #antiviral barriers to cross-species transmission of #zoonotic #influenza A viruses? @jordanbeckerphd.bsky.social @langloislab.bsky.social &co show that CpG-enriched avian #viruses are restricted by several mammalian proteins, including ZAP & KHNYN @plosbiology.org πŸ§ͺ plos.io/47fkMVp

29.10.2025 10:10 β€” πŸ‘ 7    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
Results of model fitting to the average daily fat content data from @Henderson1990-bd. a) observed average daily fat content (points) and estimated lactation curves from Wood's [-@Wood1967-re] model, a Tweedie GLM, and a Tweedie GAM (lines) with associated 95% confidence (Wood's model) or 95% credible intervals (GLM and GAM). Response residuals for Wood's model (b), Tweedie GLM (c), and Tweedie GAM (d), plus scatter plot smoothers (lines) and 95% credible intervals (shaded ribbons).

The fitted lactation curves are like an inverted U, with an extended longer tail to the right (later in lactation). The GAM curve fits the data well, but the fitted curves from Wood's model and the GLM equivalent do not provide good fits to the data, and over predict the amount of fat produced at the peak of lactation, and only grossly capture the decline in fat production later in lactation. The remaining panels show the raw response residuals for the three models, drawing attention to the poor fit; for Wood's model and the GLM there is significant pattern in the residuals, while for the GAM no residual pattern is observed.

Results of model fitting to the average daily fat content data from @Henderson1990-bd. a) observed average daily fat content (points) and estimated lactation curves from Wood's [-@Wood1967-re] model, a Tweedie GLM, and a Tweedie GAM (lines) with associated 95% confidence (Wood's model) or 95% credible intervals (GLM and GAM). Response residuals for Wood's model (b), Tweedie GLM (c), and Tweedie GAM (d), plus scatter plot smoothers (lines) and 95% credible intervals (shaded ribbons). The fitted lactation curves are like an inverted U, with an extended longer tail to the right (later in lactation). The GAM curve fits the data well, but the fitted curves from Wood's model and the GLM equivalent do not provide good fits to the data, and over predict the amount of fat produced at the peak of lactation, and only grossly capture the decline in fat production later in lactation. The remaining panels show the raw response residuals for the three models, drawing attention to the poor fit; for Wood's model and the GLM there is significant pattern in the residuals, while for the GAM no residual pattern is observed.

Quantities of interest derived from Wood's model, a Tweedie GLM, and a Tweedie GAM fitted to the lactation data example: a) the estimated week of peak average daily fat content, b) the estimated average daily fat content at the peak, and c) the rate of change (first derivative) of the lactation curve estimated at a point that is midway between the peak fat content and the end of lacation. The points are the estimated values and the lines are a 95% uncertainty interval. The uncertainty interval is based on the 0.025 and 0.975 percentiles of the bootstrap distribution of model coefficient estimates (Wood's model) or of the posterior distribution (GLM and GAM).

Each panel shows three point estimates and an uncertainty range. The three points are the estimates from a GAM, a GLM, and Wood's lactation model. The first panel shows the estimated timing of the peak of lactation, with the GAM capturing the fact that the peak in the data occurs much later in lactation (~ week 11) while the other two models confidently estimate that the peak is in week ~8-9. The GAM estimate has a much wider credible interval, which does include the estimates of Wood's model & the GLM at the extreme end. This reflects the uncertainty in the estimation of the peak timing arising from the data having a wide flat peak.

The other panels show the estimates of fat content at the peak, which are broadly similar at ~ 0.7 kg fat per day. The final panel showing the persistency estimate shows the GAM estimate diverging from those of the GLM and Wood's model. Again, the latter two models are overly confident in their estimation of this biologically relevant parameter, despite the fited lactation curve not really following the lactation data.

Quantities of interest derived from Wood's model, a Tweedie GLM, and a Tweedie GAM fitted to the lactation data example: a) the estimated week of peak average daily fat content, b) the estimated average daily fat content at the peak, and c) the rate of change (first derivative) of the lactation curve estimated at a point that is midway between the peak fat content and the end of lacation. The points are the estimated values and the lines are a 95% uncertainty interval. The uncertainty interval is based on the 0.025 and 0.975 percentiles of the bootstrap distribution of model coefficient estimates (Wood's model) or of the posterior distribution (GLM and GAM). Each panel shows three point estimates and an uncertainty range. The three points are the estimates from a GAM, a GLM, and Wood's lactation model. The first panel shows the estimated timing of the peak of lactation, with the GAM capturing the fact that the peak in the data occurs much later in lactation (~ week 11) while the other two models confidently estimate that the peak is in week ~8-9. The GAM estimate has a much wider credible interval, which does include the estimates of Wood's model & the GLM at the extreme end. This reflects the uncertainty in the estimation of the peak timing arising from the data having a wide flat peak. The other panels show the estimates of fat content at the peak, which are broadly similar at ~ 0.7 kg fat per day. The final panel showing the persistency estimate shows the GAM estimate diverging from those of the GLM and Wood's model. Again, the latter two models are overly confident in their estimation of this biologically relevant parameter, despite the fited lactation curve not really following the lactation data.

a) Estimated daily growth rate on November 15^th^, 2021 and 95% Bayesian credible interval for the 18 pigs in the pig growth example. b) Posterior distribution of daily growth rate on November 15^th^, 2021, for three pigs (numbers 2, 13, and 17), for whom weight observations ceased before November 1^st^, 2021. In b), the shaded region is the posterior distribution, the point, and thick and thin bars are the posterior median, and 66% and 95% posterior intervals respectively.

With the fitted growth curves, we can estimate for any day what the growth rate of each pig was. In this figure I'm showing the estimated growth rate of each pig in the example on November 21st. This growth rate is the first derivative of the fitted growth curve (smooth function). I used posterior sampling to produce the posterior distribution of the growth rate for each pig. These are summarised as a point estimate (median) and ccredible interval in the first panel with most pigs growin at ~1-1.5 kg per day by November 21st, with uncertainties on the order of +/- 0.5 kg per day.

The second panel shows the entire posterior distribution of the estimated growth rate for three pigs (2, 13, and 17) for whom there were no weight estimates after November 1st. Here, the model is drawing power from the other pigs to help extrapolate the growth curves for these three pigs, but pig-specific details remain, with the posterior distribution for pig 17 being much more diffuse (wider) than for either pigs 2 or 13, reflecting greater uncertainty for the former animal.

a) Estimated daily growth rate on November 15^th^, 2021 and 95% Bayesian credible interval for the 18 pigs in the pig growth example. b) Posterior distribution of daily growth rate on November 15^th^, 2021, for three pigs (numbers 2, 13, and 17), for whom weight observations ceased before November 1^st^, 2021. In b), the shaded region is the posterior distribution, the point, and thick and thin bars are the posterior median, and 66% and 95% posterior intervals respectively. With the fitted growth curves, we can estimate for any day what the growth rate of each pig was. In this figure I'm showing the estimated growth rate of each pig in the example on November 21st. This growth rate is the first derivative of the fitted growth curve (smooth function). I used posterior sampling to produce the posterior distribution of the growth rate for each pig. These are summarised as a point estimate (median) and ccredible interval in the first panel with most pigs growin at ~1-1.5 kg per day by November 21st, with uncertainties on the order of +/- 0.5 kg per day. The second panel shows the entire posterior distribution of the estimated growth rate for three pigs (2, 13, and 17) for whom there were no weight estimates after November 1st. Here, the model is drawing power from the other pigs to help extrapolate the growth curves for these three pigs, but pig-specific details remain, with the posterior distribution for pig 17 being much more diffuse (wider) than for either pigs 2 or 13, reflecting greater uncertainty for the former animal.

Just updated my manuscript on using #GAMs in #AnimalScience, now on arXiv: doi.org/10.48550/arX...
πŸ„πŸ–πŸͺΆ

Extended examples now show how GAMs go beyond prediction, helping estimate biologically meaningful traits from data.

Code: github.com/gavinsimpson...

πŸ§ͺ #RStats #mgcv #Statistics #OpenScience

29.10.2025 10:44 β€” πŸ‘ 55    πŸ” 8    πŸ’¬ 0    πŸ“Œ 0
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Structural and phenotypic plasticity of the RBD loop2 region is a key determinant for HKU5r-CoVs’ emergence in mink The emergence of novel coronaviruses from animal reservoirs continues to pose a significant zoonotic threat. Here, we investigate the evolutionary origins and virological properties of a recently repo...

New preprint alert!! 🚨🚨🚨in collaboration with the Letko @fviromics.bsky.social and Baric labs!

Just in case you're tired of sarbecoviruses, this time we looked at ACE2-using merbecoviruses! specifically the first HKU5r-CoVs detected in mink a couple of years ago.

www.biorxiv.org/content/10.1...

28.10.2025 05:06 β€” πŸ‘ 24    πŸ” 9    πŸ’¬ 1    πŸ“Œ 0
Webpage screenshot of the Black Microbiologists Association job board. The page lists five academic job postings with institution names, locations, and posting dates. Listings include Hofstra University, NYU Langone Health, University of Chicago, Rice University, and University of British Columbia. The interface features a yellow and blue theme with top navigation links labeled About Us, Membership, Directory, Events, and Newsroom. Buttons for Donate, Contact Us, and Job Board are located in the upper right corner.

Webpage screenshot of the Black Microbiologists Association job board. The page lists five academic job postings with institution names, locations, and posting dates. Listings include Hofstra University, NYU Langone Health, University of Chicago, Rice University, and University of British Columbia. The interface features a yellow and blue theme with top navigation links labeled About Us, Membership, Directory, Events, and Newsroom. Buttons for Donate, Contact Us, and Job Board are located in the upper right corner.

πŸ”¬ Microbiology job seekers 🧫 go to BMA Job Board to view open positions! Have a vacancy to fill? Posting instructions also available (scroll to bottom). blackinmicrobiology....

15.10.2025 21:33 β€” πŸ‘ 9    πŸ” 10    πŸ’¬ 1    πŸ“Œ 0
The summarised schedule of Black in Micro Week 2025, October 14-16. All times are in Eastern Standard Time. Mon 14: Pathways for Change. Welcome and Keynote Address 12pm. Marian Johnson-Thompson, PhD. Panel Discussion: Finding Black Spaces in STEM, 1:15-2:15 PM. Weds 15, Careers & Research: ECR Symposium 9-12 PM. Panel discussion: Navigating Careers in Microbiology 2-3 PM. Thurs 16, Community: Panel Discussion - Empowering Your Science 12-1:15 PM. Workshop: Science in Action

The summarised schedule of Black in Micro Week 2025, October 14-16. All times are in Eastern Standard Time. Mon 14: Pathways for Change. Welcome and Keynote Address 12pm. Marian Johnson-Thompson, PhD. Panel Discussion: Finding Black Spaces in STEM, 1:15-2:15 PM. Weds 15, Careers & Research: ECR Symposium 9-12 PM. Panel discussion: Navigating Careers in Microbiology 2-3 PM. Thurs 16, Community: Panel Discussion - Empowering Your Science 12-1:15 PM. Workshop: Science in Action

Friendly reminder: πŸŽ‰ Pre-register today & get ready to join our FREE online celebration. Everyone is welcome. To keep #BlackInMicro alive Donate: tinyurl.com/GiveBiM and Register to attend: linktr.ee/BlackInMicro (see links in bio) #BiMWeek2025

07.10.2025 21:45 β€” πŸ‘ 4    πŸ” 3    πŸ’¬ 1    πŸ“Œ 0

I have the privilege of working with fed agency folks. They've been jerked around, forced to move, had offices taken, lost resources, put on leave, fired, re-hired, *shot at*, and now furloughed. Still they return each day to help make America a bit more informed, healthier, and safer.

01.10.2025 13:48 β€” πŸ‘ 121    πŸ” 25    πŸ’¬ 2    πŸ“Œ 1
Unlocking the genomic repertoire of a cultivated megaphage - npj Viruses npj Viruses - Unlocking the genomic repertoire of a cultivated megaphage

Multiomic analysis of the only megaphage in culture. In press today.

Unlocking the genomic repertoire of a cultivated megaphage | npj Viruses share.google/HgU1cjRnaHWv...

#phage #bacteriophage

30.09.2025 13:16 β€” πŸ‘ 10    πŸ” 4    πŸ’¬ 0    πŸ“Œ 0
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LRP8 is a receptor for tick-borne encephalitis virus - Nature LRP8, an apolipoprotein E and reelin receptor with high expression in the brain, is a receptor for tick-borne encephalitis virus.

www.nature.com/articles/s41...

Stunning work from the Chandran lab!

25.09.2025 02:20 β€” πŸ‘ 13    πŸ” 6    πŸ’¬ 0    πŸ“Œ 0
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Bats live with some viruses. But others can do them in Bats can carry some deadly human pathogens without signs of illness. A new survey shows that other viruses can still be bad for bats.

www.sciencenews.org/article/bats...

23.09.2025 12:22 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

Super excited to finally share this! #CollectionsAreEssential

22.09.2025 19:50 β€” πŸ‘ 17    πŸ” 8    πŸ’¬ 0    πŸ“Œ 0
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MERS-CoV and SARS-CoV-2 infection in diverse human lung organoid-derived cultures | Journal of Virology The COVID-19 pandemic heralded the upsurge in human-derived lung organoid-based studies due to their cellular heterogeneity that partly emulates the cellular complexity of the respiratory tract. A maj...

journals.asm.org/doi/10.1128/...

21.09.2025 15:41 β€” πŸ‘ 4    πŸ” 3    πŸ’¬ 0    πŸ“Œ 0
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Molecular basis of sarbecovirus evolution and receptor tropism in natural hosts, potential intermediate hosts, and humans Kosugi et al. elucidate sarbecovirus evolution and ACE2 receptor tropism in natural hosts (12 Rhinolophus bat species), potential intermediate hosts (civets and raccoon dogs), and humans using a pseud...

Great to have this one published @cp-cellreports.bsky.social !! Some sarbecoviruses can use more ACE2 orthologs than others. The reason? A few sites in the RBD modulating the receptor usage of these viruses throughout their evolution! Worth a read πŸ‘‡πŸ‘‡πŸ‘‡

www.cell.com/cell-reports...

20.09.2025 10:37 β€” πŸ‘ 27    πŸ” 10    πŸ’¬ 0    πŸ“Œ 0
A Julia toolkit for species distribution data

Our software paper on SpeciesDistributionToolkit.jl is now published in @peercomjournal.bsky.social - peercommunityjournal.org/articles/10....

18.09.2025 15:41 β€” πŸ‘ 16    πŸ” 8    πŸ’¬ 1    πŸ“Œ 0

A single freezer inventory document that everyone must use, especially for samples! Each box has a specific position in the freezer, labeled as the location which has allowed us to recover from a freezer failure without everyone losing track of the boxes they need to find

17.09.2025 18:41 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

One of the best parts of being at a land-grant university is the chance to connect field ecology, lab virology, and public health right here in our own community. Proud to contribute local science to global questions. @wsuvetmed.bsky.social

17.09.2025 15:54 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

@stephseifertphd is following 20 prominent accounts