2026-05-19T02:59:02+00:00 http://mellislab.github.io Ian Mellis im2613@cumc.columbia.edu 2026-05-11T00:00:00+00:00 http://mellislab.github.io/positions/position/postdoc 2026-04-02T00:00:00+00:00 http://mellislab.github.io/events/k08 <p>Ian and the lab are awarded a <a href="https://reporter.nih.gov/project-details/11282444">K08</a> from NIH/NIAID. Thanks to our mentors, supporters, and NIAID!</p> 2026-04-01T00:00:00+00:00 http://mellislab.github.io/papers/paper/VYD2311 <h1 id="abstract">Abstract</h1> <p>For millions of immunocompromised individuals, vaccines may not elicit adequate protection from infections, so alternative strategies for pre-exposure prophylaxis are essential. There is only one non-vaccine product authorized in the U.S. as pre-exposure prophylaxis against COVID-19: the monoclonal antibody pemivibart. We previously showed that pemivibart had lower neutralizing activity in vitro against many recent dominant SARS-CoV-2 variants, such as KP.3.1.1, NB.1.8.1, and LP.8.1.1, than it had against JN.1, which was dominant when the antibody was first authorized. The manufacturer of pemivibart (Invivyd) recently initated clinical testing of a new monoclonal antibody derived from pemivibart, VYD2311, but there are no available studies of the activity of VYD2311 against dominant and emerging SARS-CoV-2 variants. Here, using pseudovirus neutralization assays, we measured the neutralizing activity of laboratory-synthesized VYD2311 and pemivibart against dominant and emerging SARS-CoV-2 variants, including XFG, NB.1.8.1, and the genetically distant BA.3.2.2. We found that VYD2311 potently neutralized all tested variants in vitro, dramatically more so than pemivibart. Combined with interpretation of earlier clinical trials of a parental antibody product, we conclude that VYD2311 is a promising candidate for passive immunoprophylaxis against COVID-19, particularly for those who do not respond well to vaccination.</p> 2026-03-11T00:00:00+00:00 http://mellislab.github.io/events/sofiia-joins <p>Welcome, <a href="/team/member/shapovalova-sofiia">Sofiia</a>! Sofiia is a Biotechnology Master’s student working with us this year.</p> 2026-01-03T00:00:00+00:00 http://mellislab.github.io/papers/paper/LP81MV <h1 id="abstract">Abstract</h1> <p>As SARS-CoV-2 evolves, it evades existing immunity elicited by exposure to earlier strains of the virus. In response, vaccine manufacturers have updated COVID-19 vaccines annually since 2022, though immune imprinting to the ancestral strain has blunted antibody responses to modern viral variants. In early 2025, the JN.1 subvariant LP.8.1 was dominant and manufacturers updated mRNA vaccine formulations to target LP.8.1 (LP.8.1 MV). However, by late 2025, other subvariants were dominant (XFG and NB.1.8.1) or emerging (e.g., PE.1.4, BA.3.2, PY.1.1.1) around the world. It is critical to understand the extent to which updated vaccine boosters elicit titers against both their target strain and recent variants. Further, it is important to quantify the extent to which immune imprinting continues to shape antiviral immune responses. Using pseudoviruses, we measured neutralizing antibody titers against a panel of 11 SARS-CoV-2 variants in serum samples from 36 adult participants in the United States before and approximately 1 month after LP.8.1 MV booster. We found that neutralizing antibody titers were substantially increased by the boost, with the greatest increases elicited against LP.8.1 and XFG. For the first time since 2022, post-boost titers were higher against the homologous vaccine target (LP.8.1) than against D614G (representing the ancestral strain). Combined, these results indicate that ancestral immune imprinting is mitigated to the greatest extent observed to date by LP.8.1 MV. Lastly, for a subset of participants, we measured neutralizing titers at approximately 4 months post-booster and found that LP.8.1-directed antibody titers were durable, with an estimated average half-life of approximately 66 days.</p> 2025-12-03T00:00:00+00:00 http://mellislab.github.io/events/kristin-joins <p>Welcome, <a href="/team/member/daniel-kristin">Kristin</a>! The first member of the lab gets started.</p> 2025-12-01T00:00:00+00:00 http://mellislab.github.io/events/lab-opens <p>Work in the lab begins! See our research interests <a href="/projects">here</a>.</p> 2025-11-21T00:00:00+00:00 http://mellislab.github.io/papers/paper/SARS-CoV-2CoP <h1 id="abstract">Abstract</h1> <p>Vaccination and prior infection elicit neutralizing antibodies targeting SARS-CoV-2, yet the quantitative relationship between serum antibodies and infection risk against viral variants remains uncertain, particularly in underrepresented regions. We investigated the protective correlation of pre-exposure serum neutralizing antibody levels, employing a panel of SARS-CoV-2 pseudoviruses (Omicron BA.1, Omicron BA.2, and ancestral D614G), and Spike-binding antibody levels, with symptomatic BA.1 or BA.2 SARS-CoV-2 infections and overall infection, in 345 household contacts from a SARS-CoV-2 household cohort study in Nicaragua. A four-fold increase in homotypic-neutralizing (e.g., BA.1-neutralizing vs. BA.1 exposure) titers was correlated with protection from symptomatic infections (BA.1 protection: 28% [95%CI 12-42%]; BA.2 protection: 43% [20-62%]), and ancestral-neutralizing titers were also correlated with protection from either variant, but only at higher average levels than homotypic. Mediation analyses revealed that homotypic and D614G-neutralizing antibodies mediated protection from infection and symptomatic infection both from prior infection and vaccination. These findings underscore the importance of monitoring variant-specific antibody responses and highlight that antibodies targeting circulating strains may be more predictive of protection from infection. Nevertheless, ancestral-strain-neutralizing antibodies remain relevant as a correlate of protection. Our study emphasizes the need for continued efforts to assess antibody correlates of protection.</p> 2025-10-14T00:00:00+00:00 http://mellislab.github.io/papers/paper/LP81 <h1 id="abstract">Abstract</h1> <p>SARS-CoV-2 continues to evolve, causing waves of infections. It is critical to understand the features of the virus that explain its growth advantages. Recently, SARS-CoV-2 Omicron JN.1 subvariants KP.3.1.1 and XEC were outcompeted by LP.8.1 and LP.8.1.1. Other subvariants, including LF.7.2.1 and MC.10.1, were also under monitoring. Subsequently, NB.1.8.1 and XFG became dominant. We found that serum neutralizing antibody titers against LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, and MC.10.1 were similar to XEC in 40 adults, including KP.2 monovalent mRNA vaccine recipients. NB.1.8.1 and XFG were more evasive of serum neutralization than LP.8.1.1. Neutralization by 12 monoclonal antibodies (mAbs) revealed that LP.8.1 and XFG, MC.10.1 and NB.1.8.1, and LF.7.2.1 evade different mAb classes. Lastly, the receptor-binding affinity of LP.8.1 was the highest among the tested viruses. Unlike most prior SARS-CoV-2 sublineage evolutionary trajectories, receptor-binding affinity better explained the rise of LP.8.1, while expansion of NB.1.8.1 and XFG appears correlated with enhanced antibody evasion.</p> 2025-07-04T00:00:00+00:00 http://mellislab.github.io/papers/paper/Optimizing <h1 id="abstract">Abstract</h1> <p>SARS-CoV-2 has largely evolved to resist antibody pressure, with each successive viral variant becoming more and more resistant to serum antibodies in the population. This evolution renders all previously authorized anti-spike therapeutic monoclonal antibodies inactive, and it threatens the remaining pipelines against COVID-19. We report herein the isolation of a human monoclonal antibody with a broad but incomplete SARS-CoV-2 neutralization profile, but structural analyses and mutational scanning lead to the engineering of variants that result in greater antibody flexibility while binding to the viral spike. Three such optimized monoclonal antibodies neutralize all SARS-CoV-2 strains tested with much improved potency and breadth, including against subvariants XEC and LP.8.1. The findings of this study not only present antibody candidates for clinical development against COVID-19, but also introduce an engineering approach to improve antibody activity via increasing conformational flexibility.</p> 2025-05-06T00:00:00+00:00 http://mellislab.github.io/papers/paper/KP2-2025 <h1 id="abstract">Abstract</h1> <p>COVID-19 vaccines have been updated each year since 2022 to improve protection against evolving SARS-CoV-2 variants. However, it is unclear whether a reformulation will be necessary for 2025. KP.2-based monovalent COVID-19 mRNA vaccines (KP.2 MV) were authorized for use in 2024, and they conferred substantial protection against hospitalizations caused by viral variants that emerged and dominated later, such as KP.3.1.1 and XEC. Today, LP.8.1 and its subvariant LP.8.1.1 have become dominant worldwide, particularly so in North America. Other variants, such as the LF.7 subvariant LF.7.2.1, have emerged with a growth advantage in Asia. To characterize the antigenicity of LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, and another variant under monitoring, MC.10.1, we tested serum samples from 20 individuals who recently received KP.2 MV in neutralization assays against JN.1, KP.2, KP.3, KP.3.1.1, XEC, LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, or MC.10.1 pseudoviruses. Serum neutralizing antibody titers against LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, and MC.10.1 were comparable to those against KP.3.1.1 and XEC, indicating that LP.8.1.1 and other recently dominant subvariants are antigenically similar to their predecessors. Therefore, the currently authorized KP.2 MV may not need to be updated for 2025, if the vaccine manufacturers could demonstrate comparable immunogenicity for KP.2 MV and LP.8.1-based mRNA vaccines and, of course, in the absence of an antigenically divergent SARS-CoV-2 variant emerging.</p> 2025-04-22T00:00:00+00:00 http://mellislab.github.io/papers/paper/XEC <h1 id="abstract">Abstract</h1> <p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and spread, and it remains critical to understand the functional consequences of mutations in dominant viral variants. The recombinant JN.1 subvariant XEC recently replaced KP.3.1.1 to become the most prevalent subvariant worldwide. Here, we measure the in vitro neutralization of KP.3.1.1 and XEC by human sera, monoclonal antibodies, and the soluble human ACE2 (hACE2) receptor relative to the parental subvariants KP.3 and JN.1. KP.3.1.1 and XEC are slightly more resistant (1.3- to 1.6-fold) than KP.3 to serum neutralization and antigenically similar. Both also demonstrate greater resistance to neutralization by select monoclonal antibodies and soluble hACE2, all of which target the top of the viral spike. Our findings suggest that the upward motion of the receptor-binding domain in the spike may be partially hindered by the N-terminal domain mutations in KP.3.1.1 and XEC, allowing these subvariants to better evade serum antibodies that target the viral spike in the up position and to have a growth advantage.</p> 2025-02-04T00:00:00+00:00 http://mellislab.github.io/papers/paper/KP2MV <h1 id="abstract">Abstract</h1> <p>In response to the ongoing evolution of SARS-CoV-2, COVID-19 mRNA vaccines were recently updated to encode the spike protein of the KP.2 subvariant of the JN.1 sublineage. However, the immunogenicity of KP.2-based monovalent mRNA vaccines (KP.2 MV) has yet to be fully evaluated and reported, particularly against dominant and growing viral variants KP.3.1.1 and XEC, which bear some distinct mutations from KP.2. Here we report that KP.2 MV boosters elicit robust neutralizing antibody titers in a cohort of 16 healthy adult participants against all tested variants in pseudovirus neutralization assays. The highest post-boost geometric mean titers were against older variants D614G (17,293) and BA.5 (14,358), suggestive of immune imprinting, but the post-boost titers against currently dominant or growing viruses KP.3.1.1 (1,698) and XEC (1,721) were still robust. Fold-changes in titers were highest against recent JN.1 subvariants, including JN.1, KP.2, KP.3, KP.3.1.1, and XEC, (5.8-to-7.8-fold), compared to older variants D614G and BA.5 (1.6- and 2.5-fold), which suggests that KP.2 MV boosters have at least partially mitigated immune imprinting. Overall, these results show that KP.2 MV boosters elicit robust neutralizing antibodies against dominant SARS-CoV-2 viruses.</p> 2024-09-17T00:00:00+00:00 http://mellislab.github.io/papers/paper/XBB-durability <h1 id="abstract">Abstract</h1> <p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies are substantially expanded 1 month after a shot of XBB.1.5 monovalent mRNA vaccine (XBB.1.5 MV) booster, but the durability of this response remains unknown. Here, we address this question by performing neutralization assays on four viral variants (D614G, BA.5, XBB.1.5, and JN.1) using sera from participants obtained at ∼1 month, ∼3 months, and ∼6 months post an XBB.1.5 MV booster. Our findings indicate that the resulting neutralizing antibody titers are robust and generally remain at stable levels for the study period, similar to those following XBB infection. Importantly, this durability of neutralizing antibody titers contrasts with the decline observed after a booster of the original monovalent or BA.5 bivalent mRNA vaccine. Our results are in line with the recent national data from the Centers for Disease Control and Prevention, showing that the efficacy against symptomatic SARS-CoV-2 infection is sustained for up to 4 months after an XBB.1.5 MV booster.</p> 2024-09-16T00:00:00+00:00 http://mellislab.github.io/papers/paper/JN1 <h1 id="abstract">Abstract</h1> <p>The recently dominant SARS-CoV-2 Omicron JN.1 has evolved into multiple sublineages, with recurrent spike mutations R346T, F456L, and T572I, some of which exhibit growth advantages, such as KP.2 and KP.3. We investigated these mutations in JN.1, examining their individual and combined effects on immune evasion, ACE2 receptor affinity, and in vitro infectivity. F456L increased resistance to neutralization by human sera, including those after JN.1 breakthrough infections, and by RBD class-1 monoclonal antibodies, significantly altering JN.1 antigenicity. R346T enhanced ACE2-binding affinity and modestly boosted the infectivity of JN.1 pseudovirus, without a discernible effect on serum neutralization, while T572I slightly bolstered evasion of SD1-directed mAbs against JN.1’s ancestor, BA.2, possibly by altering SD1 conformation. Importantly, expanding sublineages such as KP.2 containing R346T, F456L, and V1104L, showed similar neutralization resistance as JN.1 with R346T and F456L, suggesting V1104L does not appreciably affect antibody evasion. Furthermore, the hallmark mutation Q493E in KP.3 significantly reduced ACE2-binding affinity and viral infectivity, without noticeably impacting serum neutralization. Our findings illustrate how certain JN.1 mutations confer growth advantages in the population and could inform the design of the next COVID-19 vaccine booster.</p> 2024-08-12T00:00:00+00:00 http://mellislab.github.io/papers/paper/GRN-TA <h1 id="abstract">Abstract</h1> <p>Background: Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and conditions. How the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear.</p> <p>Results: We analyze existing bulk and single-cell transcriptomic datasets to uncover the prevalence of transcriptional adaptation in mammalian systems across diverse contexts and cell types. We perform regulon gene expression analyses of transcription factor target sets in both bulk and pooled single-cell genetic perturbation datasets. Our results reveal greater robustness in expression of regulons of transcription factors exhibiting transcriptional adaptation compared to those of transcription factors that do not. Stochastic mathematical modeling of minimal compensatory gene networks qualitatively recapitulates several aspects of transcriptional adaptation, including paralog upregulation and robustness to mutation. Combined with machine learning analysis of network features of interest, our framework offers potential explanations for which regulatory steps are most important for transcriptional adaptation.</p> <p>Conclusions: Our integrative approach identifies several putative hits—genes demonstrating possible transcriptional adaptation—to follow-up on experimentally and provides a formal quantitative framework to test and refine models of transcriptional adaptation.</p> 2024-05-31T00:00:00+00:00 http://mellislab.github.io/papers/paper/BA2-87-1 <h1 id="abstract">Abstract</h1> <p>As SARS-CoV-2 continues to spread and mutate, tracking the viral evolutionary trajectory and understanding the functional consequences of its mutations remain crucial. Here, we characterized the antibody evasion, ACE2 receptor engagement, and viral infectivity of the highly mutated SARS-CoV-2 Omicron subvariant BA.2.87.1. Compared with other Omicron subvariants, including EG.5.1 and the current predominant JN.1, BA.2.87.1 exhibits less immune evasion, reduced viral receptor engagement, and comparable infectivity in Calu-3 lung cells. Intriguingly, two large deletions (Δ15-26 and Δ136-146) in the N-terminal domain (NTD) of the spike protein facilitate subtly increased antibody evasion but significantly diminish viral infectivity. Collectively, our data support the announcement by the USA CDC that the public health risk posed by BA.2.87.1 appears to be low.</p> 2024-03-13T00:00:00+00:00 http://mellislab.github.io/papers/paper/XBBMV <h1 id="abstract">Abstract</h1> <p>COVID-19 vaccines have recently been updated to specifically encode or contain the spike protein of the SARS-CoV-2 XBB.1.5 subvariant, but their immunogenicity in humans has yet to be fully evaluated and reported, particularly against emergent viruses that are rapidly expanding. We now report that administration of an updated monovalent mRNA vaccine booster (XBB.1.5 MV) to previously uninfected individuals boosted serum virus-neutralizing antibodies significantly against not only XBB.1.5 (27.0-fold increase) and EG.5.1 (27.6-fold increase) but also key emerging viruses such as HV.1, HK.3, JD.1.1, and JN.1 (13.3- to 27.4-fold increase). Individuals previously infected by an Omicron subvariant had the highest overall serum neutralizing titers (ID50 1,504–22,978) against all viral variants tested. While immunological imprinting was still evident with the updated vaccines, it was not nearly as severe as observed with the previously authorized bivalent BA.5 vaccine. Our findings strongly support the official recommendation to widely apply the updated COVID-19 vaccines.</p> 2024-02-21T00:00:00+00:00 http://mellislab.github.io/papers/paper/iPSC-Jain <h1 id="abstract">Abstract</h1> <p>Pluripotency can be induced in somatic cells by the expression of OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis increased the reprogramming efficiency. We provide evidence for a unified model in which cells can move into and out of the primed state over time, explaining how reprogramming appears deterministic at short time scales and stochastic at long time scales. Furthermore, inhibiting the activity of LSD1 enlarged the pool of cells that were primed for reprogramming. Thus, even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.</p> 2023-11-17T00:00:00+00:00 http://mellislab.github.io/papers/paper/BA2-75 <h1 id="abstract">Abstract</h1> <p>SARS-CoV-2 Omicron BA.2.75 has diversified into multiple subvariants with additional spike mutations and several are expanding in prevalence, particularly CH.1.1 and BN.1. Here, we investigated the viral receptor affinities and neutralization evasion properties of major BA.2.75 subvariants actively circulating in different regions worldwide. We found two distinct evolutionary pathways and three newly identified mutations that shaped the virological features of these subvariants. One phenotypic group exhibited a discernible decrease in viral receptor affinities, but a noteworthy increase in resistance to antibody neutralization, as exemplified by CH.1.1, which is apparently as resistant as XBB.1.5. In contrast, a second group demonstrated a substantial increase in viral receptor affinity but only a moderate increase in antibody evasion, as exemplified by BN.1. We also observed that all prevalent SARS-CoV-2 variants in the circulation presently, except for BN.1, exhibit profound levels of antibody evasion, suggesting this is the dominant determinant of virus transmissibility today.</p> 2023-07-19T00:00:00+00:00 http://mellislab.github.io/papers/paper/fatemap <h1 id="abstract">Abstract</h1> <p>Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.</p> 2023-03-29T00:00:00+00:00 http://mellislab.github.io/papers/paper/BA5BV-3mo <h1 id="abstract">Abstract</h1> <p>Bivalent mRNA vaccine boosters expressing Omicron BA.5 spike and ancestral D614G spike were introduced to attempt to boost waning antibody titers and broaden coverage against emerging SARS-CoV-2 lineages. Previous reports showed that peak serum neutralizing antibody (NAb) titers against SARS-CoV-2 variants following bivalent booster were similar to peak titers following monovalent booster. It remains unknown whether these antibody responses would diverge over time. We assessed serum virus-neutralizing titers in 41 participants who received three monovalent mRNA vaccine doses followed by bivalent booster, monovalent booster, or BA.5 breakthrough infection at one month and three months after the last vaccine dose or breakthrough infection using pseudovirus neutralization assays against D614G and Omicron subvariants (BA.2, BA.5, BQ.1.1, and XBB.1.5). There was no significant difference at one month and three months post-booster for the two booster cohorts. BA.5 breakthrough patients exhibited significantly higher NAb titers at three months against all Omicron subvariants tested compared against monovalent and bivalent booster cohorts. There was a 2-fold drop in mean NAb titers in the booster cohorts between one and three month time points, but no discernible waning of titers in the BA.5 breakthrough cohort over the same period. Our results suggest that NAb titers after boosting with one dose of bivalent mRNA vaccine are not higher than boosting with monovalent vaccine. Perhaps inclusion of D614G spike in the bivalent booster exacerbates the challenge posed by immunological imprinting. Hope remains that a second bivalent booster could induce superior NAb responses against emerging variants.</p> 2022-04-05T00:00:00+00:00 http://mellislab.github.io/papers/paper/iPSC-CM-diff <h1 id="abstract">Abstract</h1> <p>Background: Cardiac differentiation of human-induced pluripotent stem (hiPS) cells consistently produces a mixed population of cardiomyocytes and non-cardiac cell types, even when using well-characterized protocols. We sought to determine whether different cell types might result from intrinsic differences in hiPS cells prior to the onset of differentiation.</p> <p>Results: By associating individual differentiated cells that share a common hiPS cell precursor, we tested whether expression variability is predetermined from the hiPS cell state. In a single experiment, cells that shared a progenitor were more transcriptionally similar to each other than to other cells in the differentiated population. However, when the same hiPS cells were differentiated in parallel, we did not observe high transcriptional similarity across differentiations. Additionally, we found that substantial cell death occurs during differentiation in a manner that suggested all cells were equally likely to survive or die, suggesting that there is no intrinsic selection bias for cells descended from particular hiPS cell progenitors. We thus wondered how cells grow spatially during differentiation, so we labeled cells by expression of marker genes and found that cells expressing the same marker tended to occur in patches. Our results suggest that cell type determination across multiple cell types, once initiated, is maintained in a cell-autonomous manner for multiple divisions.</p> <p>Conclusions: Altogether, our results show that while substantial heterogeneity exists in the initial hiPS cell population, it is not responsible for the variability observed in differentiated outcomes; instead, factors specifying the various cell types likely act during a window that begins shortly after the seeding of hiPS cells for differentiation.</p> 2022-04-04T00:00:00+00:00 http://mellislab.github.io/projects/project/04-cell-engineering <p>Complex cellular interactions and gene regulatory patterns shape the emergence and long-term functioning of the many different cell types in the human body. We are interested in developing and applying quantitative models of the regulation of cellular identity (a.k.a. cell type) at a molecular level. Relatedly, we are interested in designing protocols for reprogramming and transdifferentiation (directing cells to progenitor or other differentiated types, respectively). We <a href="/papers/paper/P3">made progress toward this goal</a> for more efficient fibroblast-to-iPSC reprogramming by suppressing genes that may be needed to maintain fibroblast identity. Currently, we are pursing theoretical and experimental projects about how cells make tradeoffs in single-cell gene expression patterns to balance regulation of their diverse functions, mapping pre-manipulation cell states to cell engineering protocol outcomes, and how to use our insights to improve cell therapies for cancers, autoimmune disorders, and regenerative applications.</p> 2022-04-04T00:00:00+00:00 http://mellislab.github.io/projects/project/03-gene-regulation <p>Diverse forms of gene regulation underpin genotype-to-phenotype maps. We aim to discover mechanisms of gene regulation and harness them for genetic engineering and gene therapy applications, developing experimental and computational methods along the way. In Ian’s PhD thesis, he invented a single-molecule RNA FISH-based tool for visualizing and quantifying <a href="/papers/paper/inoFISH">RNA editing</a> with sub-single-cell resolution and he contributed to the development of other specialized RNA FISH-based methods for <a href="/papers/paper/clampFISH">amplifying RNA FISH</a> signal and for visualizing <a href="/papers/paper/tissueSNPFISHbursting">allelic expression</a> in tissues. More recently, we published a study about <a href="/papers/paper/GRN-TA">transcriptional adaptation</a>, a gene regulatory phenomenon that allows organisms to compensate for mutations. We are pursuing projects related to modeling gene regulatory networks and leveraging transcriptional adaptation for genetic engineering.</p> 2022-04-04T00:00:00+00:00 http://mellislab.github.io/projects/project/02-virus-evolution <p>Viruses evolve under a variety of selective pressures, and predicting evolutionary trajectories is a major goal in the field. We are most interested in how viruses balance the trade-offs associated with mutation-induced evasion of existing adaptive immune responses and changes to critical host cell entry mechanisms, most recently explored in the context of SARS-CoV-2 (<a href="/papers/paper/LP81">8</a>, <a href="/papers/paper/XEC">9</a>, <a href="/papers/paper/JN1">10</a>, <a href="/papers/paper/BA2-87-1">11</a>, <a href="/papers/paper/BA2-75">12</a>). We use rapid engineering of BSL-2-rated pseudoviruses combined with epidemiological data mining, phylogenetic analysis, and biophysical modeling to predict near-term evolutionary trajectories and dynamics. We are pursuing projects related to predicting the evolution of SARS-CoV-2 and other pathogens, engineering immune-evasive gene therapy vectors, and more.</p> 2022-04-04T00:00:00+00:00 http://mellislab.github.io/projects/project/01-virus-neutralizing-antibodies <p>Antibodies protect us from infections, and eliciting potent neutralizing antibody responses is a core goal of most vaccination programs. We have extensively characterized the breadth and potency of SARS-CoV-2-directed antibodies elicited by COVID-19 vaccines and infections (<a href="/papers/paper/LP81MV">1</a>, <a href="/papers/paper/SARS-CoV-2CoP">2</a>, <a href="/papers/paper/KP2-2025">3</a>, <a href="/papers/paper/KP2MV">4</a>, <a href="/papers/paper/XBB-durability">5</a>, <a href="/papers/paper/XBBMV">6</a>, <a href="/papers/paper/BA5BV-3mo">7</a>) using BSL-2-rated pseudovirus neutralization assays, human cohort studies, mouse models, and related specialized techniques. We have also <a href="/papers/paper/Optimizing">isolated, engineered</a>, and <a href="/papers/paper/VYD2311">characterized</a> a variety of monoclonal SARS-CoV-2-neutralizing antibodies. Scientifically, this work has dissected the impacts of <a href="/papers/paper/LP81MV">immune imprinting</a> on adaptive immune responses to evolving pathogens. Translationally, these studies have been important in vaccine development and regulatory decision-making, with some of our <a href="/papers/paper/KP2-2025">work</a> featured in CDC scientists’ <a href="https://www.fda.gov/advisory-committees/advisory-committee-calendar/vaccines-and-related-biological-products-advisory-committee-may-22-2025-meeting-announcement#event-materials">presentation</a> at a VRBPAC meeting. We are pursuing projects about vaccine development, monoclonal antibody development, and more.</p> 2021-08-04T00:00:00+00:00 http://mellislab.github.io/papers/paper/P3 <h1 id="abstract">Abstract</h1> <p>Identifying the particular transcription factors that maintain cell type in vitro is important for manipulating cell type. Identifying such transcription factors by their cell type-specific expression or their involvement in developmental regulation has had limited success. We hypothesized that because cell type is often resilient to perturbations, the transcriptional response to perturbations would reveal identity-maintaining transcription factors. We developed Perturbation Panel Profiling (P3) as a framework for perturbing cells across many conditions and measuring gene expression responsiveness transcriptome-wide. In human iPSC-derived cardiac myocytes, P3 showed that transcription factors important for cardiac myocyte differentiation and maintenance were among the most frequently up-regulated (most responsive). We reasoned that one function of responsive genes may be to maintain cellular identity. We identified responsive transcription factors in fibroblasts using P3 and found that suppressing their expression led to enhanced reprogramming. We propose that responsiveness to perturbations is a property of transcription factors that help maintain cellular identity in vitro.</p> 2021-05-17T00:00:00+00:00 http://mellislab.github.io/papers/paper/AMIAcovid <h1 id="abstract">Abstract</h1> <p>As of August 2020, there were ~6 million COVID-19 cases in the United States of America, resulting in ~200,000 deaths. Informatics approaches are needed to better understand the role of individual and community risk factors for COVID-19. We developed an informatics method to integrate SARS-CoV-2 data with multiple neighborhood-level factors from the American Community Survey and opendataphilly.org. We assessed the spatial association between neighborhood-level factors and the frequency of SARS-CoV-2 positivity, separately across all patients and across asymptomatic patients. We found that neighborhoods with higher proportions of individuals with a high-school degree and/or who were identified as Hispanic/Latinx were more likely to have higher SARS-CoV-2 positivity rates, after adjusting for other neighborhood covariates. Patients from neighborhoods with higher proportions of individuals receiving public assistance and/or identified as White were less likely to test positive for SARS-CoV-2. Our approach and its findings could inform future public health efforts.</p> 2021-01-04T00:00:00+00:00 http://mellislab.github.io/papers/paper/melanoma-screen <h1 id="abstract">Abstract</h1> <p>Cellular plasticity describes the ability of cells to transition from one set of phenotypes to another. In melanoma, transient fluctuations in the molecular state of tumor cells mark the formation of rare cells primed to survive BRAF inhibition and reprogram into a stably drug-resistant fate. However, the biological processes governing cellular priming remain unknown. We used CRISPR-Cas9 genetic screens to identify genes that affect cell fate decisions by altering cellular plasticity. We found that many factors can independently affect cellular priming and fate decisions. We discovered a new plasticity-based mode of increasing resistance to BRAF inhibition that pushes cells towards a more differentiated state. Manipulating cellular plasticity through inhibition of DOT1L before the addition of the BRAF inhibitor resulted in more therapy resistance than concurrent administration. Our results indicate that modulating cellular plasticity can alter cell fate decisions and may prove useful for treating drug resistance in other cancers.</p> 2020-04-14T00:00:00+00:00 http://mellislab.github.io/misc/home/home <p>Our research spans a broad range of topics related to pathogenic viruses, gene and cell therapies, and adaptive immune responses. We integrate diverse approaches from the fields of molecular systems biology, virology, and immunology to study gene regulation, build methods for genetic engineering, characterize virus evolution, propose vaccine candidates, engineer gene therapies, and mitigate immune responses that interfere with gene and cell therapies.</p> <p>We are affiliated with the <a href="https://www.pathology.columbia.edu">Department of Pathology and Cell Biology</a> and the <a href="https://www.adarc.cuimc.columbia.edu">Aaron Diamond AIDS Research Center</a> at the <a href="https://www.cuimc.columbia.edu/">Columbia University Irving Medical Center</a>.</p> <p>Interested in learning more? See our <a href="/projects/">research interests</a> and <a href="/papers/">publications</a> to read about our latest work. Check out <a href="/events/">news</a> for lab events, honors, and updates.</p> <p>We emphasize interdisciplinary collaboration and personalized mentorship, and we’re always on the lookout for motivated candidates interested in <a href="/positions/">joining the group</a>.</p> 2020-04-14T00:00:00+00:00 http://mellislab.github.io/misc/donate <h1 id="donate-to-the-lab">Donate to the lab</h1> <div class="row"> <div class="col-md-7"> <h4 id="your-gift-to-the-lab-will">Your gift to the lab will:</h4> <ul> <li>Support a cutting-edge research program that aims to better understand virus evolution and human immune responses, and to improve gene and cell therapies</li> <li>Further the education of the next generation of scientists</li> <li>Help produce approaches, tools, and data that can benefit the worldwide scientific community in immunology research and beyond</li> </ul> <h4 id="to-make-a-donation-please-follow-these-steps">To make a donation, please follow these steps:</h4> <ul> <li>pending instructions</li> <li>As a final step, please let us know about your gift in an email to <a href="mailto:im2613@cumc.columbia.edu">im2613@cumc.columbia.edu</a> so that we can follow up and thank you for your kind and generous donation!</li> </ul> <p><strong>Thank you for considering giving to the Mellis Lab!</strong></p> </div></div> 2020-04-14T00:00:00+00:00 http://mellislab.github.io/misc/contact <h1 id="contact">Contact</h1> <h3 id="lab-address">Lab Address</h3> <p>Ian Mellis<br /> Columbia University<br /> 701 W. 168th St.<br /> HHSC 1116<br /> New York, NY 10032</p> <h3 id="primary-contact">Primary Contact</h3> <p>Ian Mellis <br /> <a href="mailto:im2613@cumc.columbia.edu">im2613@cumc.columbia.edu</a></p> 2020-04-14T00:00:00+00:00 http://mellislab.github.io/misc/about <h1 id="credit">Credit</h1> <p>Our lab website’s design and implementation is based on the framework built by <a href="http://bedford.io/team/trevor-bedford/">Trevor Bedford</a> at the Fred Hutchinson Cancer Research Center, which he has made freely available on <a href="https://github.com/blab/blotter">GitHub</a> and which has been employed as the foundation for many other academic sites. Our site’s code base began with a fork of <a href="http://getzlab.org/team/principal%20investigator/getz-gad">Gad Getz</a>’s lab webiste (built from a fork of <a href="http://drummondlab.org/team/d-allan-drummond">Allan Drummond</a>’s lab <a href="http://drummondlab.org">website</a>, which was itself heavily inspired by the Bedford Lab website). Like the Bedford, Drummond, and Getz lab websites, our site is built with <a href="http://jekyllbootstrap.com">Jekyll Bootstrap</a>, a static site generator, and like the Drummond Lab site, is deployed using <a href="https://pages.github.com/">GitHub Pages</a>.</p> <p>Our site’s source code is freely available on <a href="https://github.com/mellislab/mellislab.github.io">GitHub</a>. All code is placed under the MIT license. You’re welcome to borrow / repurpose code to build your own site, and if you do, we’d appreciate attribution and links back to <a href="http://mellislab.github.io">mellislab.github.io</a>, <a href="http://www.getzlab.org">getzlab.org</a>, <a href="http://drummondlab.org">drummondlab.org</a>, and <a href="http://bedford.io">bedford.io</a>.</p> <p>Some of the images on this website are from <a href="https://bioart.niaid.nih.gov/">NIAID NIH Bioart Source</a>, <a href="https://www.goyallab.org/">Yogesh Goyal</a>, and <a href="https://www.infectiousdiseases.cuimc.columbia.edu/profile/yicheng-guo-phd">Yicheng Guo</a>. I am grateful to <a href="/team/co-mentee/wu-maddie">Maddie Wu</a> for creating the Mellis Lab logo.</p> 2019-01-09T00:00:00+00:00 http://mellislab.github.io/papers/paper/matrix-melanoma <h1 id="abstract">Abstract</h1> <p>Physical changes in skin are among the most visible signs of aging. We found that young dermal fibroblasts secrete high levels of extracellular matrix (ECM) constituents, including proteoglycans, glycoproteins, and cartilage-linking proteins. The most abundantly secreted was HAPLN1, a hyaluronic and proteoglycan link protein. HAPLN1 was lost in aged fibroblasts, resulting in a more aligned ECM that promoted metastasis of melanoma cells. Reconstituting HAPLN1 inhibited metastasis in an aged microenvironment, in 3-D skin reconstruction models, and in vivo. Intriguingly, aged fibroblast-derived matrices had the opposite effect on the migration of T cells, inhibiting their motility. HAPLN1 treatment of aged fibroblasts restored motility of mononuclear immune cells, while impeding that of polymorphonuclear immune cells, which in turn affected regulatory T-cell recruitment. These data suggest that although age-related physical changes in the ECM can promote tumor cell motility, they may adversely affect the motility of some immune cells, resulting in an overall change in the immune microenvironment. Understanding the physical changes in aging skin may provide avenues for more effective therapy for older patients with melanoma. SIGNIFICANCE: These data shed light on the mechanochemical interactions that occur between aged skin, tumor, and immune cell populations, which may affect tumor metastasis and immune cell infiltration, with implications for the efficacy of current therapies for melanoma.</p> 2019-01-03T00:00:00+00:00 http://mellislab.github.io/papers/paper/tissueSNPFISHbursting <h1 id="abstract">Abstract</h1> <p>Extensive cell-to-cell variation exists even among putatively identical cells, and there is great interest in understanding how the properties of transcription relate to this heterogeneity. Differential expression from the two gene copies in diploid cells could potentially contribute, yet our ability to measure from which gene copy individual RNAs originated remains limited, particularly in the context of tissues. Here, we demonstrate quantitative, single molecule allele-specific RNA FISH adapted for use on tissue sections, allowing us to determine the chromosome of origin of individual RNA molecules in formaldehyde-fixed tissues. We used this method to visualize the allele-specific expression of Xist and multiple autosomal genes in mouse kidney. By combining these data with mathematical modeling, we evaluated models for allele-specific heterogeneity, in particular demonstrating that apparent expression from only one of the alleles in single cells can arise as a consequence of low-level mRNA abundance and transcriptional bursting.</p> 2018-11-12T00:00:00+00:00 http://mellislab.github.io/papers/paper/clampFISH <h1 id="abstract">Abstract</h1> <p>Methods for detecting single nucleic acids in cell and tissues, such as fluorescence in situ hybridization (FISH), are limited by relatively low signal intensity and non-specific probe binding. Here we present click-amplifying FISH (clampFISH), a method for fluorescence detection of nucleic acids that achieves high specificity and high-gain (&gt;400x) signal amplification. ClampFISH probes form a “C” configuration upon hybridization to the sequence of interest in a double helical manner. The ends of the probes are ligated together using bioorthogonal click chemistry, effectively locking the probes around the target. Iterative rounds of hybridization and click amplify the fluorescence intensity. We show that clampFISH enables the detection of RNA species with low magnification microscopy and in RNA-based flow cytometry. Additionally, we show that the modular design of clampFISH probes allows multiplexing of RNA and DNA detection, that the locking mechanism prevents probe detachment in expansion microscopy, and that clampFISH can be applied in tissue samples.</p> 2017-06-12T00:00:00+00:00 http://mellislab.github.io/papers/paper/inoFISH <h1 id="abstract">Abstract</h1> <p>Conversion of adenosine to inosine is a frequent type of RNA editing, but important details about its biology remain unknown due to a lack of imaging tools. We developed inoFISH to directly visualize and quantify adenosine-to-inosine edited transcripts in situ. We found that editing of GRIA2, EIF2AK2, and NUP43 is uncorrelated with nuclear localization and paraspeckle association. Further, NUP43 exhibits constant editing levels between single cells while GRIA2 levels vary.</p> 2016-01-26T00:00:00+00:00 http://mellislab.github.io/papers/paper/ADPDD <h1 id="abstract">Abstract</h1> <p>Biomarkers from multiple modalities have been shown to correlate with cognition in Parkinson’s disease (PD) and in Alzheimer’s disease (AD). However, the relationships of these markers with each other, and the use of multiple markers in concert to predict an outcome of interest, are areas that are much less explored. Our objectives in this study were (1) to evaluate relationships among 17 biomarkers previously reported to associate with cognition in PD or AD and (2) to test performance of a five-biomarker classifier trained to recognize AD in identifying PD with dementia (PDD). To do this, we evaluated a cross-sectional cohort of PD patients (n = 75) across a spectrum of cognitive abilities. All PD participants had 17 baseline biomarkers from clinical, genetic, biochemical, and imaging modalities measured, and correlations among biomarkers were assessed by Spearman’s rho and by hierarchical clustering. We found that internal correlation among all 17 candidate biomarkers was modest, showing a maximum pairwise correlation coefficient of 0.51. However, a five-marker subset panel derived from AD (CSF total tau, CSF phosphorylated tau, CSF amyloid beta 42, APOE genotype, and SPARE-AD imaging score) discriminated cognitively normal PD patients vs. PDD patients with 80% accuracy, when employed in a classifier originally trained to recognize AD. Thus, an AD-derived biomarker signature may identify PDD patients with moderately high accuracy, suggesting mechanisms shared with AD in some PDD patients. Based on five measures readily obtained during life, this AD-derived signature may prove useful in identifying PDD patients most likely to respond to AD-based crossover therapies.</p> 2015-10-31T00:00:00+00:00 http://mellislab.github.io/papers/paper/GenRes2015 <h1 id="abstract">Abstract</h1> <p>Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines.</p> 2013-08-20T00:00:00+00:00 http://mellislab.github.io/papers/paper/COIN <h1 id="abstract">Abstract</h1> <p>Conditional mutagenesis is becoming a method of choice for studying gene function, but constructing conditional alleles is often laborious, limited by target gene structure, and at times, prone to incomplete conditional ablation. To address these issues, we developed a technology termed conditionals by inversion (COIN). Before activation, COINs contain an inverted module (COIN module) that lies inertly within the antisense strand of a resident gene. When inverted into the sense strand by a site-specific recombinase, the COIN module causes termination of the target gene’s transcription and simultaneously provides a reporter for tracking this event. COIN modules can be inserted into natural introns (intronic COINs) or directly into coding exons as part of an artificial intron (exonic COINs), greatly simplifying allele design and increasing flexibility over previous conditional KO approaches. Detailed analysis of over 20 COIN alleles establishes the reliability of the method and its broad applicability to any gene, regardless of exon-intron structure. Our extensive testing provides rules that help ensure success of this approach and also explains why other currently available conditional approaches often fail to function optimally. Finally, the ability to split exons using the COIN’s artificial intron opens up engineering modalities for the generation of multifunctional alleles.</p> 2012-12-31T00:00:00+00:00 http://mellislab.github.io/portals/portal/gtexportal <p>GTEx Project Portal</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/co-mentee/wu-maddie <p>Maddie is a Lab Technician in Dr. David D. Ho’s lab in the Aaron Diamond AIDS Research Center at Columbia University. Maddie graduated from Princeton University in 2021, where she received a degree in East Asian Studies and Music Theater. She wrote her academic thesis on East Asian Representation through Music in American Musical Theater from the 1950s to the present. Maddie then joined Teach for America, where she was placed as a 1st grade teacher on the west side of Oahu. Inspired by her experiences in teaching and her desire to address health disparities present in the local community, she then career-changed and completed her post-baccalaureate pre-med requirements at Bryn Mawr College. She is excited to pursue a career as a physician and is grateful to Dr. Mellis for his mentorship.</p> <p>Outside the lab, you can usually catch Maddie at a soccer field, watching the Phil, or at a theater. She is also a proud Michigander and an avid Michigan sports fan.</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/member/shapovalova-sofiia <p>Sofiia is a Master’s student in the Biotechnology program at Columbia, doing research into COVID-19 strain mutations for her dissertation, and her interests are immune engineering and vaccine/cancer therapeutics.</p> <p>Sofiia studied biochemistry at undergraduate studies, where she became interested in learning more about the applications of immunology to study human disease. In her master’s degree at UCL, she applied her knowledge of molecular pathways of disease to research the effect of including toll-like receptor 9 (TLR9) adjuvants in mRNA-based lipid nanoparticles (LNPs). During her studies at Columbia, she further refined her immunological knowledge when studying the application of the immune system to develop viable therapeutic targets to cure infectious diseases and cancer in the Immunoengineering with Biomaterials and Nanotechnology class. During her research position at the Mellis Lab, she is excited to apply her skills and knowledge to research and study the role of evolving COVID-19 strain mutations in guiding knowledge into development of novel future therapeutics and vaccines.</p> <p>Outside of her studies, Sofiia is interested in playing tennis, snowboarding, and traveling.</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/principal%20investigator/mellis-ian <p>Ian is an Assistant Professor of Pathology and Cell Biology and a member of the Aaron Diamond AIDS Research Center at Columbia University. Clinically, he is Assistant Director of the NewYork-Presbyterian/Columbia Cellular Therapy Laboratory and an Attending Physician in Transfusion Medicine and Cellular Therapy.</p> <p>Ian studied mathematics, molecular biology, and bioinformatics at Amherst College, where he wrote an interdisciplinary thesis about the molecular evolution of RNA interference pathway components. He then completed M.D. and Ph.D. training in the University of Pennsylvania Medical Scientist Training Program. His Ph.D. in Genomics and Computational Biology advised by Arjun Raj involved developing experimental and computational systems biology approaches to studying post-transcriptional gene regulation and engineering cellular identity. Ian then moved to Columbia/NewYork-Presbyterian for research-track Clinical Pathology residency training followed by Transfusion Medicine fellowship at the New York Blood Center and Columbia. Throughout residency and fellowship, Ian conducted postdoctoral research at Columbia. He initiated independent collaborations with Yogesh Goyal about gene regulatory networks and then joined the lab of David Ho, where he built expertise in virology and adaptive immunity.</p> <p>Outside of science and medicine, Ian loves taking his toddler on adventures around NYC, cooking, and learning languages.</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/co-mentee/huang-chihiro <p>Chihiro is a fourth-year M.D. student at National Taiwan University, currently a visiting scholar in the David Ho Lab. In Taiwan, she previously conducted research in the Department of Microbiology, where she led a project on telomere maintenance in patients with Parkinson’s disease, and in the Department of Emergency Medicine, where she worked on implementing AI models to identify antibiotic-resistant pathogens in the emergency room setting. Prior to joining the Aaron Diamond AIDS Research Center, she collaborated with Dr. Bertrand Lebouché in the Department of Family Medicine at McGill University to develop an AI chatbot for patients living with HIV. She has also completed internships at Abbott and several biomedical startups across California and Taiwan.</p> <p>Outside of medicine and research, Chihiro enjoys eating and drinking across NYC, discovering jazz and R&amp;B, and calling her younger sister in Tokyo.</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/co-mentee/hong-hsiang <p>Hsiang (Shawn) is an M.D./Ph.D. trainee at National Taiwan University and a visiting scholar in Dr. David D. Ho’s lab in the Aaron Diamond AIDS Research Center at Columbia University. His research specializes in translational virology and immunology, with a focus on antibody discovery, viral evolution, and the development of immunomodulating antiviral therapeutics. Advised by David Ho and co-mentored by Ian, his ongoing Ph.D. thesis explores emerging pathogen surveillance, antigenic tracking, and therapeutic development for viral diseases including influenza, SARS-CoV-2, and HIV.</p> <p>Outside of medicine and science, Hsiang can usually be found on a volleyball court, exploring coffee shops and restaurants across NYC, or drinking matcha with a book in the park.</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/friend/goyal-yogesh <p>Yogesh is an Assistant Professor of Cell and Developmental Biology and a member of the Center for Synthetic Biology at Northwestern University. Scientifically, he has a multidisciplinary background, including undergraduate training in chemical engineering, graduate research in quantitative developmental biology, and postdoctoral experience in single-cell biology. Yogesh leads an interdisciplinary, collaborative, vibrant, and supportive research team. Outside of research, Yogesh enjoys sports, drawing and engaging in art-science projects, pumpkin spice lattes, and bantering with Ian.</p> 1970-01-01T00:00:00+00:00 http://mellislab.github.io/team/member/daniel-kristin <p>Kristin studied Chemical and Biomedical Engineering at Carnegie Mellon Univerity, along with a concentration in Cellular and Molecular Biotechnology and a minor in International Relations and Politics. While at Carnegie Mellon, she worked in the Wayne Macrophage Lab on a project related to Preeclampsia. After, she recieved a Fulbright Fellowship to continue investigating the condition in the UK. During her Fulbright, she completed an MSc in Health Research Methods and a dissertation related to transcriptomic differences between early and late onset preeclampsia.</p> <p>Outside of the lab, Kristin loves reading, long runs/walks, and exploring local hole-in-the-wall resturants.</p>