• slidebg1
    Welcome to the Salis Lab at Penn State University
    We develop predictive biophysical models and design algorithms
    to rationally engineer synthetic genetic systems and organisms
    for Synthetic Biology and Metabolic Engineering applications
  • slidebg1
    Welcome to the Salis Lab at Penn State University
    We engineer bacteria, yeast, and algae to add new metabolic and sensing capabilities.
    Our software has designed over 50,000 synthetic DNA sequences for biotech researchers around the world.
    Photo credit: ChiamYu Ng

Fundamental Research Questions

The Biophysics of Gene Expression and Regulation

An organism's genes control its cellular fate: metabolism, self-replication, development, pathogenesis, and disease. Gene expression levels are controlled by multiple layers of biomolecular interactions with its genetic template. With so many coupled interactions, it remains a challenge to predict how DNA mutations affect gene expression levels.


In the Salis Lab, we develop and experimentally validate biophysical models that predict an organism's gene expression levels from its DNA sequence. Each model is highly reductionist, focusing on specific biomolecular interactions that control transcription rate, translation rate, or their regulation. We formulate low-parameter models using statistical thermodynamics and kinetics, parameterize them using rationally designed series of experiments, and validate their predictions across hundreds of experiments using diverse DNA sequence sets. We then create user-friendly web interfaces so that the Life Science community can use our biophysical models of gene expression for their own studies.

Design and Optimization of Synthetic Genetic Systems

The functions of simple micro-organisms are ultimately determined by their DNA sequences. By redesigning those sequences, we can engineer micro-organisms to become distributed sensor networks, active signal processing agents, chemically computing decision-makers, and nano-sized chemical factories. In practice, there are an astronomical number of design choices (different DNA sequences), but only a relatively few will yield a successfully engineered micro-organism.

In the Salis Lab, we develop computational algorithms that allow researchers to rationally design and efficiently optimize the DNA sequences of engineered micro-organisms. Our algorithms design very specific DNA sequences that yield well-predicted gene expression levels inside the cell, enabling researchers to combine and control multiple genes together in a reliable fashion. Our algorithms enable researchers to increase recombinant protein expression, design sensors for diverse chemicals, efficiently optimize metabolic pathways, and program sophisticated decision-making genetic circuits.

Synthetic Biology and Metabolic Engineering Applications

Engineering Cellular Sensors

Micro-organisms can be engineered to detect and respond to specific chemicals with applications in medical diagnostics, CBE detection, and environmental remediation. Using a biophysical model of riboswitches (RNA-based sensors), we have rationally designed and engineered cell sensors for drugs, metabolites, toxins, explosives, hormones, and neurotransmitters. We have also engineered natural sensors that employ transcriptional regulation to sense important chemicals.

Engineering Genetic Circuits

Genetic circuits combine multiple gene regulators to perform signal processing and decision-making. We use our biophysical models to rationally engineer synthetic genetic circuits with desired input-output transformations. We have created a series of signal amplification circuits to enhance the dynamic range of a cellular sensors. We have also developed new approaches to experimentally measure the intrinsic binding affinities of transcription factors, which becomes necessary to predict, control, and optimize their gene regulatory behaviors.

Engineering Metabolic Networks and Pathways

We rationally engineer and introduce new metabolic pathways into organisms and efficiently optimize their biosynthetic capacities. We have engineered a 3-enzyme terpenoid biosynthesis pathway to demonstrate our new approach to pathway optimization; a 5-enzyme Entner-Doudoroff pathway to rapidly regenerate the essential cofactor NADPH; and a 6-enzyme furfural catabolic pathway to remove a toxic microbial inhibitor found in lignocellulosic feedstock. Our design algorithms allow new researchers to quickly design, build, and optimize metabolic pathways with a high rate of success.

Engineering Synthetic Genomes

As our engineered genetic systems have grown in size, we now routinely integrate them into the organism's genome to ensure their stability and self-replication. We've combined our rational design methods with the latest genome engineering techniques -- MAGE and CRISPR/Cas9 -- to snip, slice, and prune an organism's genome with desired knock-up and knock-down of its gene expression levels. Say goodbye to plasmids!

The RBS Calculator v2.0

Predicts the translation initiation rates of natural bacterial mRNA sequences (validated in many bacterial hosts).

Designs synthetic ribosome binding sites for targeted translation initiation rates.

The RBS Library Calculator

Designs the smallest size library of ribosome binding sites to uniformly vary a bacterial protein's expression level.

Designs maximally informative genetic system variants for efficiently finding a system's optimal protein expression levels.

The Operon Calculator

Predicts the expression levels of proteins within a multi-cistronic operon (translation rates, translational coupling rates, and mRNA stability changes).

Designs the mRNA sequence of a multi-cistronic operon for maximal expression control over its proteins.

The Riboswitch Calculator

Predicts changes in expression from translation-regulating riboswitches in bacteria.

Designs synthetic riboswitches that bind to specific chemicals with the highest possible expression level change.

The Small RNA Calculator

Predicts changes in expression from translation-regulating regulatory RNAs in bacteria.

The Pathway Map Calculator

Maps the relationship between DNA sequence, enzyme expression level, and pathway productivity for a multi-enzyme metabolic pathway, while using the smallest number of characterization experiments.

Predicts the optimal enzyme expression levels of a multi-enzyme pathway, using a sequence-expression-activity map (SEA MAP).

Advancing the Engineering Science of Synthetic Biology

Who Uses Our Models and Algorithms?

6300

Registered Users

67108

Sequences Designed

320

Universities

53

Countries

14

Industrial Licensees

7

Undergraduate Courses

Meet the Lab

  • Howard's picture

    Prof. Howard Salis

    / Principle Investigator
    salis at psu.edu

    ...

  • Manish's picture

    Manish Kushwaha

    / Post-doctoral Fellow
    manish.kushwaha at psu.edu

    ...

  • Amin's picture

    Amin Espah Borujeni

    / Graduate Student
    aue130 at psu.edu

    ...

  • Iman's picture

    Iman Farasat

    / Graduate Student
    izf101 at psu.edu

    ...

  • ChiamYu's picture

    Chiam Yu Ng

    / Graduate Student
    cun121 at psu.edu

    ChiamYu is re-engineering cellular metabolism from the bottom-up, and developing new design methods to accelerate that process. She is also an avid photographer and musician.

  • Tian's picture

    Tian Tian

    / Graduate Student
    tit5090 at psu.edu

    ...

  • Long's picture

    Long Chen

    / Graduate Student
    luc161 at psu.edu

    ...

  • Alex's picture

    Alexander Reis

    / Graduate Student
    acr219 at psu.edu

    Alex is developing advanced sequence-to-function biophysical models of gene expression and regulation for prokayotes and eukaryotes. His hobbies include rowing, weight lifting, reading, creative projects, and PC building.

    Grace Vezeau

    / Graduate Student
    gev107 at psu.edu

    Grace is engineering RNA-based sensors for applications in metabolic engineering, toxicology, medical diagnostics, and environmental remediation. In her free time, she enjoys hiking, skiing, and a good cup of coffee.

    Sean Halper

    / Graduate Student
    sxh456 at psu.edu

    Sean is developing next-generation approaches to engineering synthetic metabolic pathways with many enzymes and synthetic genetic circuits with many regulators. In his spare time, Sean enjoys tabletop games, videogames, and sleep.

Lab Photos and Videos

Photo1

Aren't blue light trans-illuminators great? And your DNA is A-OK!

Photo2

Tian admires her stack of agar plates.

Photo3

Is this engineering or artistry? Or both!

Photo4

Iman designs a genetic system using our algorithms.

Photo5

A Lab Outing to Hershey Park in the Dark.

This was a fun one!

Our Publications

Espah Borujeni A., D.M. Mishler, J. Wang, W. Huso, and H.M. Salis. Automated Physics-based Design of Synthetic Riboswitches from Diverse Aptamers, Nature Biotechnology, in review

...

Tian T. and H.M. Salis. A Biophysical Model of Translational Coupling to Coordinate and Control Protein Expression in Bacterial Operons, Nucleic Acid Research, in review

...

Kushwaha M. and H.M. Salis. A Portable Power Supply for Cross-Species Engineering of Genetic Circuits and Metabolic Pathways, Nature Communications, in review

...

Ng C.Y., I. Farasat, C. Maranas, and H.M. Salis. Rational Design of a Synthetic Entner-Doudoroff pathway for Improved and Controllable NADPH Regeneration, Metabolic Engineering, v29

...

Farasat, I., Kushwaha M., Collens J., Easterbrook M., Guido M., and Salis H.M. Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria, Molecular Systems Biology, v10 (6)

...

Espah Borujeni, A., Channarasappa A.S., and Salis H.M. Translation Rate is Controlled by Coupled Trade-offs between Site Accessibility, Selective RNA unfolding and Sliding at Upstream Standby Sites, Nucleic Acid Research, v41 (21)

...

Salis, H.M. The Ribosome Binding Site Calculator, Methods in Enzymology, v498, pp. 19-42

...

Salis, H.M., Mirsky, E.A. and Voigt, C.A. Automated Design of Synthetic Ribosome Binding Sites to Control Protein Expression, Nature Biotechnology, v27 (10)

...

Tabor, J.J., Salis, H.M., Simpson, Z.B., Chevalier, A.A., Levskaya, A., Marcotte, E., Voigt, C.A., and Ellington, A.D. A Synthetic Genetic Edge Detection Program, Cell, 137 (7): 1271-1281

...

Groban, E.S., Clarke, E.J., Salis, H.M, Miller, S.M., and Voigt, C.A. Kinetic Buffering of Crosstalk between Bacterial Two-component Sensors, Journal of Molecular Biology, 390 (3): 380-393.

...

Salis H.M., Tamsir A., and Voigt C.A. Engineering Bacterial Signals and Sensors, Bacterial Sensing and Signaling, Contributions to Microbiology series, Collin M. and Schuch R. (eds)

...

Temme, K., Salis, H., Tullman-Ercek, D. Levskaya, A., Hong, S-H., and Voigt, C. A. Induction and Relaxation Dynamics of the Regulatory Network Controlling the Type III Secretion System Encoded within Salmonella Pathogenicity Island 1, Journal of Molecular Biology, 377 (1): 47-61.

...

H. Salis and Y. Kaznessis. Computer Aided Design of Modular Protein Devices: Logical AND Gene Activation, Physical Biology, v3 (4).

...

H. Salis, V. Sotiropoulos, and Y. Kaznessis. Multiscale Hy3S: Hybrid Stochastic Simulation for Supercomputers, BMC Bioinformatics, v7. (Highly accessed)

...

L. Tuttle, H. Salis, J. Tomshine, and Y. Kaznessis. Model-Driven Designs of an Oscillating Gene Network, Biophysical Journal, v89(6).

...

H. Salis, and Y. Kaznessis. An Equation-free Probabilistic Steady State Approximation: Dynamic Application to the Stochastic Simulation of Biochemical Reaction Networks, Journal of Chemical Physics, v123 (21).

...

H. Salis, and Y. Kaznessis. Accurate Hybrid Stochastic Simulation of a System of Coupled Chemical or Biochemical Reactions, Journal of Chemical Physics, v122(5).

...

H. Salis, and Y. Kaznessis. Numerical Simulation of Stochastic Gene Circuits, Computers in Chemical Engineering, v29(3).

...

H.M. Salis. Simulation of Stochastic Chemical Systems: Applications in the Design and Construction of Synthetic Gene Networks, Ph.D. Thesis, Chemical Engineering, University of Minnesota.

Lab News

  • Howard speaks at ICBE

    Howard presents the lab's recent work on "Automated Design of Synthetic Riboswitches from Diverse RNA Aptamers" at the International Conference on Biomolecular Engineerign in Austin, TX. It was an excellent conference.

  • New Graduate Students, Welcome!

    Sean Halper and Alexander Reis have joined the Salis lab as first-year Chemical Engineering graduate students. Welcome!

  • Tian speaks at AIChE

    Tian Tian presented her recent research results at AIChE's Annual Meeting in Atlanta, GA, entitled "Autonomous Control of Metabolism with Synthetic Sensor-Circuits".

  • Chiam Yu speaks at AIChE

    ChiamYu Ng presented her recent research results at the AIChE's Annual Meeting in Atlanta, GA, entitled "Design & Optimization of a Synthetic Entner-Doudoroff Pathway for Efficient NADPH Regeneration".

  • Howard speaks at Indo-US Workshop on Synthetic Biology

    Howard traveled to New Delhi, India and presented the lab's unique, model-oriented approach to engineering synthetic organisms at the NSF-sponsored Indo-US Workshop for Systems and Synthetic Biology.

  • Howard presents a seminar at Genomatica Inc.

    Howard presented the lab's approach to efficiently engineering metabolic pathways at Genomatica's headquarters in San Diego, CA.

  • Howard presents a seminar at CalTech

    Howard presented an overview of the lab's Synthetic Biology research during the Chemical Engineering seminar series at the California Institute of Technology.

  • ChiamYu Wins SynBERC Award!

    ChiamYu Ng wins the Best Presentation Award at the SynBERC Fall Retreat for her presentation on "Design and Optimization of a Synthetic Entner-Doudoroff Pathway for Improved and Controllable NADPH Regeneration".

  • New Lab Space!

    The Salis Lab has moved to a new laboratory space in the Wartik building!

  • New Graduate Student, Welcome!

    Grace Vezeau has joined the Salis lab as a first-year Biological Engineering graduate student. Welcome!

  • Howard speaks at SIMB's Annual Meeting

    Howard presents the lab's recent research results on "The Design and Optimization of a Synthetic Entner-Doudoroff Pathway for Efficient NADPH Regeneration" at the Society for Industrial Microbiology and Biotechnology's annual meeting in St. Louis, MO.

  • Howard speaks at the Amazon AWS Government and Educational Symposium in D.C.

    Howard shared the lab's experiences with translating research results into a user-friendly Software-as-a-Service using AWS' distributing computing system.

  • A New Grant to Design Genetic Circuits!

    The Salis Lab has received a grant from the Air Force Office of Scientific Research to develop a theory-based genetic compiler that designs advanced synthetic genetic circuits.

  • Howard speaks at Q-Bio Winter conference

    >Howard shares the lab's recent research on "White-Boxing Genetic Circuit Modeling: Absolute TF Binding Free Energies From Fluorescence Measurements" at the Quantitative-bio Winter conference in Kona Island, HI.

  • Amin Presents at AIChE

    >Amin Espah Borujeni presents his work on the "Riboswitch Calculator: De Novo Design of Synthetic Cis-Acting Riboswitches From Ligand-Binding Aptamers" at the AIChE Annual Meeting in San Francisco.

  • Iman Presents at AIChE

    Iman Farasat presents his work on "White-Boxing Genetic Circuit Modeling: Absolute TF Binding Free Energies From Fluorescence Measurements" at the AIChE Annual Meeting in San Francisco.

  • Iman Wins SynBERC Award

    Iman Farasat wins the Best Poster Award at the SynBERC Fall Retreat for his work on "Single-pass design of genetic circuits using in vivo measurements of transcription factor binding energies".

  • A New Grant to Design Sensors and Genetic Circuits!

    The Salis Lab has received a grant from the Office of Naval Research to engineer advanced cellular sensors and signal processing genetic circuits.

  • ChiamYu Ng Wins Penn State Award!

    Chiam Yu Ng wins the Best Candidacy Exam Award. Congratulations!

  • Howard speaks at SIMB Annual Meeting

    Howard presents the lab's research results on the "Efficient Design and Optimization of Genetic Circuits and Metabolic Pathways" at the Society for Industrial Microbiology and Biotechnology in San Diego, CA.

  • Howard Receives the NSF Career Award

    Howard has received the NSF Career Award to develop next-generation approaches for metabolic pathway engineering.

  • Howard Presents an Invited Talk at IWBDA in London

    Howard Salis presents an invited talk, "Clone Less, Know More: Efficient Design and Optimization of Genetic Circuits and Metabolic Pathways" at the International Workshop on Bio-design Automation in London.

  • Long Chen Defends his Masters Thesis. Congratulations!

    Long Chen has successfully defended his Masters Thesis on a molecular lock and key system to control DNA replication. Congratulations!

  • New Graduate Student, Welcome!

    Chiam Yu Ng has joined the Salis lab as a first-year Chemical Engineering graduate student. Welcome!

  • Tian Tian Presents Her Work at SynBERC!

    Tian Tian presents her work on a "Biophysical Model of Translational Coupling to Coordinate Protein Expression" at the SynBERC Fall Retreat.

  • A New Grant to Design Advanced Sensors and Genetic Circuits!

    The Salis lab has received an ONR MURI grant to develop advanced cell-based sensors and signal processing genetic circuits.

  • Tian Tian Defends her Masters Thesis. Congratulations!

    Tian Tian has successfully defended her Masters Thesis on a new biophysical model of translational coupling, and will be continuing as a PhD student. Congratulations!

  • A New Grant to Build a Genetic Security System

    The Salis lab has received a DARPA grant to develop a genetic security system for recombinant DNA.

  • New Graduate Students, Welcome!

    Tian Tian and Long Chen have joined the Salis lab as first-year Biological Engineering graduate students. Welcome!

  • Iman Wins Penn State Award!

    Iman Farasat has received the Leighton Riess Graduate Fellowship in Engineering for outstanding work. Congratulations!

  • Howard Receives DARPA Young Faculty Award

    Howard has received the DARPA Young Faculty Award for the "Rational Design of Nucleic Acids to Control Metabolism".

  • New Graduate Students, Welcome!

    Amin Espah Borujeni and Iman Farasat have joined the Salis lab as first-year Chemical Engineering graduate students. Welcome!

Resident Education at Penn State University

BE 302: Transport Processes for Biological Systems

A junior-level required course. The fundamentals of fluid mechanics, heat transfer, and mass transfer are applied to biological systems at scales ranging from microbial to ecological. This course includes a weekly 2-hour lab. Past lecture notes are available here.

ChE 340: Introduction to Biomolecular Engineering

A junior/senior-level required course. Design principles for engineering biological systems are introduced, with a focus on biotechnology and pharmaceutical applications. This course covers the engineering of proteins, metabolism, and genetic circuits using kinetics, thermodynamics, bioinformatics, and genetic engineering techniques.

ChE 410: Mass Transfer and Separations

A senior-level required course. Introduction to principles and applications of mass transfer with a focus on the design of equilibrium staged and continuously contacting separation processes.

BE 297 | ChE 297: Introduction to Synthetic Biology and Genetic Engineering

An undergraduate elective course. An introductory course on designing and modeling small genetic systems -- sensors, regulators, and enzymes -- that reprogram an organism's behavior towards making cellular decisions and manufacturing chemical products.

BE 597 | ChE 597: Synthetic Biology. Programming Life.

A graduate-level elective course. An in-depth course on designing and modeling synthetic genetic circuits to carry out Boolean decision-making, analog feedback control, and programmed decision-making. Several literature examples are discussed. Stochastic and deterministic modeling approaches are reviewed and applied to example systems.

Undergraduate Research Projects

  • International Genetically Engineered Machine Contest (iGEM). 2010-present.
  • NSF Research Experience for Undergraduates: Chemical Energy Storage and Conversion. 2010-2013.
  • NSF Research Experience for Undergraduates: Biologically Inspired Catalytic Materials. 2014-present.

Join the Salis Lab

We are currently recruiting graduate students from the Biological Engineering and Chemical Engineering departments. Please apply to their respective graduate programs, and contact Howard for more information on research topics.