About

Stephen C. Harrison is a Professor of Biological Chemistry and Molecular Pharmacology who has played a central role in guiding Harvard's Biochemical Sciences Tutorial Program for decades, including serving as Head Tutor from 1972-1996. His contributions emphasize the importance of teaching students how to think about scientific problems and how discoveries emerge from evidence. Harrison's work has been instrumental in shaping the tutorial's focus on developing scientific thinking through discussion of primary literature, fostering intellectual relationships between students and practicing scientists, and mentoring students toward research and honors projects. His involvement reflects a commitment to advancing undergraduate education in the life sciences by promoting critical thinking, evidence-based understanding, and professional development.

Research topics

• Biology
• Evolutionary biology
• Molecular biology
• Ecology
• Computational biology
• Genetics

Selected publications

• Emergence of activation or repression in transcriptional control under a fixed molecular context

  Proceedings of the National Academy of Sciences · 2025-09-22 · 5 citations

  articleOpen accessSenior authorCorresponding

  Transcription factors (TFs) can be both activators and repressors of gene transcription. This can manifest as "duality," where the transcriptional response increases (activation) with TF concentration in one context but decreases (repression) in another context, or as "nonmonotonicity," where, in the same context, the response increases in part of the concentration range and decreases outside that range. Here we use biophysical models of gene regulation to investigate how duality and nonmonotonicity relate to the interactions between a TF, Polymerase and the regulatory DNA. We distinguish two modes of TF action on Polymerase: "coherent," with interactions either positive or negative, and "incoherent," where interactions are a mix of both. For TFs that act incoherently from a single TF-DNA binding site, nonmonotonicity can arise, but only under nonequilibrium models. For single-site models, we show that nonmonotonicity can never happen under the common thermodynamic models of gene regulation, which consider equilibrium conditions and ignore the dissipative nature of the transcription process. Moreover, we show that merely changing the TF-DNA binding affinity, while keeping other features fixed, can tune the response between activation and repression, with responses either evaluated as a function of TF concentration or site number. Using the mammalian Sp1 as a case study and synthetically designed target sequences, we find experimental evidence for nonmonotonicity, and activation or repression tuned by affinity, which we interpret as evidence of incoherent action. Our work highlights the importance of moving from a TF-centric view to a systems view when reasoning about transcriptional control.

  PublisherOA PDFDOI

• Emergence of activation or repression in transcriptional control under a fixed molecular context

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-06-02 · 11 citations

  preprintOpen accessSenior author

  For decades, studies have noted that transcription factors (TFs) can behave as either activators or repressors of different target genes. More recently, evidence suggests TFs can act on transcription simultaneously in positive and negative ways. Here we use biophysical models of gene regulation to define, conceptualize and explore these two aspects of TF action: "duality", where TFs can be overall both activators and repressors at the level of the transcriptional response, and "coherent and incoherent" modes of regulation, where TFs act mechanistically on a given target gene either as an activator or a repressor (coherent) or as both (incoherent). For incoherent TFs, the overall response depends on three kinds of features: the TF's mechanistic effects, the dynamics and effects of additional regulatory molecules or the transcriptional machinery, and the occupancy of the TF on DNA. Therefore, activation or repression can be tuned by just the TF-DNA binding affinity, or the number of TF binding sites, given an otherwise fixed molecular context. Moreover, incoherent TFs can cause non-monotonic transcriptional responses, increasing over a certain concentration range and decreasing outside the range, and we clarify the relationship between non-monotonicity and common assumptions of gene regulation models. Using the mammalian SP1 as a case study and well controlled, synthetically designed target sequences, we find experimental evidence for incoherent action and activation, repression or non-monotonicity tuned by affinity. Our work highlights the importance of moving from a TF-centric view to a systems view when reasoning about transcriptional control.

  PublisherOA PDFDOI

• The Hill function is the universal Hopfield barrier for sharpness of input–output responses

  Proceedings of the National Academy of Sciences · 2024-05-24 · 10 citations

  articleOpen access

  The Hill functions, [Formula: see text], have been widely used in biology for over a century but, with the exception of [Formula: see text], they have had no justification other than as a convenient fit to empirical data. Here, we show that they are the universal limit for the sharpness of any input-output response arising from a Markov process model at thermodynamic equilibrium. Models may represent arbitrary molecular complexity, with multiple ligands, internal states, conformations, coregulators, etc, under core assumptions that are detailed in the paper. The model output may be any linear combination of steady-state probabilities, with components other than the chosen input ligand held constant. This formulation generalizes most of the responses in the literature. We use a coarse-graining method in the graph-theoretic linear framework to show that two sharpness measures for input-output responses fall within an effectively bounded region of the positive quadrant, [Formula: see text], for any equilibrium model with [Formula: see text] input binding sites. [Formula: see text] exhibits a cusp which approaches, but never exceeds, the sharpness of [Formula: see text], but the region and the cusp can be exceeded when models are taken away from thermodynamic equilibrium. Such fundamental thermodynamic limits are called Hopfield barriers, and our results provide a biophysical justification for the Hill functions as the universal Hopfield barriers for sharpness. Our results also introduce an object, [Formula: see text], whose structure may be of mathematical interest, and suggest the importance of characterizing Hopfield barriers for other forms of cellular information processing.

  PublisherOA PDFDOI

• The Hill function is the universal Hopfield barrier for sharpness of input-output responses

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-03-28 · 2 citations

  preprintOpen access

  Abstract The Hill functions, ℋ h ( x ) = x h / (1 + x h ), have been widely used in biology for over a century but, with the exception of ℋ 1 , they have had no justification other than as a convenient fit to empirical data. Here, we show that they are the universal limit for the sharpness of any input-output response arising from a Markov process model at thermodynamic equilibrium. Models may represent arbitrary molecular complexity, with multiple ligands, internal states, conformations, co-regulators, etc, under core assumptions that are detailed in the paper. The model output may be any linear combination of steady-state probabilities, with components other than the chosen input ligand held constant. This formulation generalises most of the responses in the literature. We use a coarse-graining method in the graph-theoretic linear framework to show that two sharpness measures for input-output responses fall within an effectively bounded region of the positive quadrant, Ω m ⊂ (ℝ + ) 2 , for any equilibrium model with m input binding sites. Ω m exhibits a cusp which approaches, but never exceeds, the sharpness of ℋ m but the region and the cusp can be exceeded when models are taken away from thermodynamic equilibrium. Such fundamental thermodynamic limits are called Hopfield barriers and our results provide a biophysical justification for the Hill functions as the universal Hopfield barriers for sharpness. Our results also introduce an object, Ω m , whose structure may be of mathematical interest, and suggest the importance of characterising Hopfield barriers for other forms of cellular information processing.

  PublisherOA PDFDOI

• Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

  Cell Systems · 2023 · 33 citations

  Senior authorCorresponding
  • Biology
  • Computational biology
  • Ecology
  PublisherOA PDFDOI

• Transcriptional activators in the early Drosophila embryo perform different kinetic roles

  Cell Systems · 2023-04-01 · 12 citations

  letterOpen accessSenior authorCorresponding
  PublisherOA PDFDOI

• Transcriptional activators in the early Drosophila embryo perform different kinetic roles

  Zenodo (CERN European Organization for Nuclear Research) · 2022-05-16 · 1 citations

  articleOpen accessSenior author

  This archive contains source data files for Figs. 1B, C, D; 2B; 3B, C, E, F; and all Supplementary Figs. <br> These data (signal intervals) are reported in .dat files. These are what were used in all analysis. <br> They each contain a data structure with several members. Each member is either a matrix of analyzed data or a string describing the columns of each matrix. These files pertain to individual experiments as follows: format:<br> [imaging directory reference] - [.dat file] eve2:wt data:<br> Experimental replicates:<br> 190726 - t1p53k<br> 190815 - t1p61e2 Photobleaching data (eve2:wt):<br> 1 frame every 60s:<br> 211027 - t1p71g2.dat<br> 1 frame every b15s:<br> 211026 - t1p71l2.dat eve2:neutral data:<br> Experimental replicates:<br> 210910 - t1p68g2<br> 190809 - t1p58k2<br> 190712 - t1p51m<br> 190808 - t1p58f eve2[Zld]:neutral data:<br> 180917 - t1p40n<br> 191024 - t1p59m eve2[Bcd]:neutral data:<br> 181002 - t1p38k<br> 191106 - t1p62e2 eve2[Dst]:neutral data:<br> 180914 - t1p37m<br> 191122 - t1p63e2 See Github repository for the scripts used to analyze these data (DOI available in manuscript) v2 introduces a different .dat file for one eve2[Zld]:neutral replicate (t1p59m.dat) and updates the title to conform with that of the published manuscript.

  PublisherDOI

• Defining kinetic roles of transcriptional activators in the early Drosophila embryo source image files (part 2)

  Zenodo (CERN European Organization for Nuclear Research) · 2022-02-28

  articleOpen accessSenior author

  This archive is related to https://doi.org/10.5281/zenodo.6312884 It contains source image files for Figs. 1B, C, D; 2B; 3B, C, E, F; and all Supplementary Figs. <br> These image files are (in part) the raw data from which the data files in https://doi.org/10.5281/zenodo.6312884 were derived. These images pertain to individual experiments as follows: format:<br> [imaging date (file prefix)] - [.dat file] eve2:wt data:<br> Experimental replicates:<br> 190726 - t1p53k<br> 190815 - t1p61e2 Photobleaching data (eve2:wt):<br> 1 frame every 60s:<br> 211027 - t1p71g2.dat<br> 1 frame every b15s:<br> 211026 - t1p71l2.dat eve2:neutral data:<br> Experimental replicates:<br> 210910 - t1p68g2<br> 190809 - t1p58k2<br> 190712 - t1p51m<br> 190808 - t1p58f eve2[Zld]:neutral data:<br> 180917 - t1p40n<br> 191024 - t1p59e2 eve2[Bcd]:neutral data:<br> 181002 - t1p38k<br> 191106 - t1p62e2 eve2[Dst]:neutral data:<br> 180914 - t1p37m<br> 191122 - t1p63e2 See Github repository for the scripts used to analyze these data (DOI available in manuscript)

  PublisherDOI

• Defining kinetic roles of transcriptional activators in the early Drosophila embryo

  Zenodo (CERN European Organization for Nuclear Research) · 2022-02-28

  articleOpen accessSenior author

  This archive contains source data files for Figs. 1B, C, D; 2B; 3B, C, E, F; and all Supplementary Figs. <br> These data (signal intervals) are reported in .dat files. These are what were used in all analysis. <br> They each contain a data structure with several members. Each member is either a matrix of analyzed data or a string describing the columns of each matrix. These files pertain to individual experiments as follows: format:<br> [imaging directory reference] - [.dat file] eve2:wt data:<br> Experimental replicates:<br> 190726 - t1p53k<br> 190815 - t1p61e2 Photobleaching data (eve2:wt):<br> 1 frame every 60s:<br> 211027 - t1p71g2.dat<br> 1 frame every b15s:<br> 211026 - t1p71l2.dat eve2:neutral data:<br> Experimental replicates:<br> 210910 - t1p68g2<br> 190809 - t1p58k2<br> 190712 - t1p51m<br> 190808 - t1p58f eve2[Zld]:neutral data:<br> 180917 - t1p40n<br> 191024 - t1p59e2 eve2[Bcd]:neutral data:<br> 181002 - t1p38k<br> 191106 - t1p62e2 eve2[Dst]:neutral data:<br> 180914 - t1p37m<br> 191122 - t1p63e2 See Github repository for the scripts used to analyze these data (DOI available in manuscript)

  PublisherDOI

• Defining kinetic roles of transcriptional activators in the early Drosophila embryo source image files (in part)

  Zenodo (CERN European Organization for Nuclear Research) · 2022-02-28

  articleOpen accessSenior author

  This archive is related to https://doi.org/10.5281/zenodo.6312884 It contains source image files for Figs. 1B, C, D; 2B; 3B, C, E, F; and all Supplementary Figs. <br> These image files are (in part) the raw data from which the data files in https://doi.org/10.5281/zenodo.6312884 were derived. These images pertain to individual experiments as follows: format:<br> [imaging date (file prefix)] - [.dat file] eve2:wt data:<br> Experimental replicates:<br> 190726 - t1p53k<br> 190815 - t1p61e2 Photobleaching data (eve2:wt):<br> 1 frame every 60s:<br> 211027 - t1p71g2.dat<br> 1 frame every b15s:<br> 211026 - t1p71l2.dat eve2:neutral data:<br> Experimental replicates:<br> 210910 - t1p68g2<br> 190809 - t1p58k2<br> 190712 - t1p51m<br> 190808 - t1p58f eve2[Zld]:neutral data:<br> 180917 - t1p40n<br> 191024 - t1p59e2 eve2[Bcd]:neutral data:<br> 181002 - t1p38k<br> 191106 - t1p62e2 eve2[Dst]:neutral data:<br> 180914 - t1p37m<br> 191122 - t1p63e2 See Github repository for the scripts used to analyze these data (DOI available in manuscript)

  PublisherDOI

Recent grants

• CAREER: Developmental Network Architecture Underlies Patterning Precision and Robustness

  NSF · $500k · 2015–2022

• NIH Grant U01GM103804

  NIH · $1.5M · 2017

• Collaborative Research: NSF/MCB: Kinetic Control of the Transcription Cycle Revealed by Synthetic Enhancers

  NSF · $700k · 2017–2020

• Multi-scale modeling of genetic variation in a developmental network

  NIH · $489k · 2013–2017

• Information Integration and Energy Expenditure in Eukaryotic Gene Regulation

  NIH · $3.7M · 2017–2025

Frequent coauthors

• Meghan D. J. Bragdon

  Boston University

  78 shared

• Zeba Wunderlich

  Boston University

  75 shared

• Ben J. Vincent

  Center for Systems Biology

  73 shared

• Javier Estrada

  67 shared

• Clarissa Scholes

  Harvard University

  40 shared

• Timothy T. Harden

  Center for Systems Biology

  40 shared

• Jeremy Gunawardena

  Harvard University

  34 shared

• Kelly M. Biette

  Arrien Pharmaceuticals (United States)

  33 shared

Labs

• Harvard’s Biochemical Sciences Tutorial ProgramPI

Awards & honors

• NSF CAREER Award