Quantitative Fundamentals of Molecular and Cellular Bioengineering

Citation

Wittrup, K. D., Tidor, B., Hackel, B. J., & Sarkar, C. A. (2020). Quantitative Fundamentals of Molecular and Cellular Bioengineering. MIT Press.

Chapter Summary

The book has nine chapters in about 570 pages of text. The publisher describes it as a presentation for chemical and biological engineers that develops dynamic models of biomolecular and cellular phenomena: it describes the molecular and cellular events behind biological function, builds models to study them, and shows by example how the models are used to design and interpret experiments. The order runs from the smallest scale to the cellular, adding complexity step by step with a focus on experimental tests of mechanistic hypotheses. Most chapters include case studies built on published research papers, a list of suggestions for further reading, and problems.

Chapter 1: Introduction to Biological Rate Processes

The opening chapter (about 27 pages) motivates rate-process models: what biological rate processes are, why a model is worth developing, how a mechanistic model is formulated, and how it is validated. The validation section names consistency with experiment, comparison with alternative models, prediction and falsifiability, and parameter sensitivity analysis. It closes with basic themes: steady state versus equilibrium, perturbations, rate forms, and characteristic time and length scales.

Chapter 2: Noncovalent Binding Interactions

A long chapter (about 80 pages) that covers kinetic rate constants, thermodynamics (state functions, free energy and standard states), and the energetic contributions to binding affinity: electrostatics, hydrogen bonding, van der Waals interactions, the hydrophobic effect, and deformation energy and entropy. It goes on to protein binding interfaces and thermodynamic cycle analysis, environmental effects on binding rate (the Arrhenius relationship, transition state theory, electrostatic effects) and light-matter measurements, with a section on fluorescence applications. Four case studies are included.

Chapter 3: Binding Equilibria and Kinetics

The longest chapter after Chapter 7 (about 100 pages). It begins with the monovalent binding isotherm and binding kinetics, then moves to multiple binding sites (independent sites, cooperativity, avidity and effective concentration, and bivalent binding at cell surfaces). The later sections cover methods for measuring binding (relaxation kinetics, biosensors, microplate immunoassays, microfluidic assays, dialysis, optical spectroscopy, isothermal titration calorimetry) and end with fitting models to data: nonlinear least squares, confidence intervals on fitted parameters, and global fitting.

Chapter 4: Enzyme Kinetics

Enzymes as catalysts and their rate laws (Michaelis-Menten, bisubstrate kinetics, substrate inhibition, cooperative enzymes, pH and temperature effects), followed by reversible inhibition including pharmacological and tight-binding inhibitors. The later sections apply the kinetics to signalling pathways (tyrosine kinases, G proteins and G protein-coupled receptors), metabolism (flux-control coefficients, constraint-based models) and hydrolytic regulatory enzymes (caspases, blood coagulation cascades, extracellular metalloproteases).

Chapter 5: Gene Expression and Protein Trafficking

The chapter treats synthesis, degradation and growth, including pure delays in biosynthesis, and then compartmental models of protein sorting, with receptor-ligand trafficking and vesicular transport.

Chapter 6: Network Dynamics

Nonlinear dynamics first, then switches and thresholds (ultrasensitivity through homomultimerization, molecular titration and zero-order effects, and bistable switches), adaptation (negative feedback, incoherent feedforward and other topologies) and oscillations, with the cell cycle and circadian rhythms as examples.

Chapter 7: Population Growth and Death Models

The longest chapter (about 100 pages). It starts with typical growth curves, then limits on the growth of cell cultures, bioreactors (the Monod chemostat and fed-batch fermentors), cell and organismal death, and compartmental growth models, which include cell cycle models, in vivo cell populations, epidemics and infections, and mixed populations.

Chapter 8: Coupled Transport and Reaction

Transport effects on binding, two-step binding, the Smoluchowski diffusion limit and surfaces, followed by scaling analyses of tissue penetration, compartmental models (the mass-transfer coefficient and pharmacokinetic models), and macromolecular crowding.

Chapter 9: Discrete Stochastic Processes

Poisson statistics, stochastic simulation (Gillespie methods and approximations), stochastic gene expression, stochasticity in phage infection, diffusion and random walks, and combinatorial bioinformatics.

Key Concepts

Chapters 1–3: Rate processes and binding

• Mechanistic model formulation and validation: building a model from a hypothesised mechanism and testing it.
• Binding affinity, thermodynamics and kinetics: equilibrium and rate descriptions of noncovalent binding.
• Cooperativity and avidity: behaviour of multiple binding sites.
• Nonlinear least squares: fitting models to data with confidence intervals.

Chapters 4–6: Enzymes, expression and networks

• Michaelis-Menten rate law: the basic enzymatic rate expression.
• Compartmental models: protein sorting and trafficking treated as connected compartments.
• Ultrasensitivity, bistability, adaptation and oscillation: the behaviours analysed in network dynamics.

Chapters 7–9: Populations, transport and stochasticity

• Growth curves and the chemostat: population growth and bioreactor models.
• Coupled transport and reaction: transport effects on binding, scaling analysis and crowding.
• Gillespie simulation: exact stochastic simulation, with approximate methods.

Critical Analysis

Strengths

• A clear modelling thread. Chapter 1 sets out how a mechanistic model is formulated and validated, and later chapters return to that process for binding, enzymes, networks, populations, transport and stochastic events.
• Case studies from the literature. Chapters 2 to 9 include case studies based on published papers, from the Luria–Delbrück study of bacterial mutation (1943) to a 2017 study of mutation effects predicted from sequence covariation, tying the models to experiments.
• Practical measurement and fitting. Chapter 3 includes methods for measuring binding and a section on fitting models to data with confidence intervals, so the book treats data analysis as part of the subject.
• Range. The nine chapters span molecules, signalling networks, populations, transport and stochastic processes within one framework, and each chapter ends with problems and suggestions for further reading.

Limitations

• Selective scope. The contents cover binding, enzyme kinetics, expression and trafficking, network dynamics, growth, transport and stochastic processes; it is not a survey of bioengineering and does not include chapters on, for example, biomaterials or medical devices.
• Substantial length and density. At about 570 pages with long chapters on binding (Chapter 3) and growth (Chapter 7), a one-term course must select among them.
• Requires background. The publisher aims it at advanced undergraduate and graduate courses in chemical engineering and bioengineering, so readers need quantitative preparation as well as some molecular biology.

Where It Fits in the Course

Within the course's list, this book is the quantitative treatment of molecular and cellular processes. Ann Saterbak, Ka-Yiu San and Larry McIntire's Bioengineering Fundamentals is a first course organised around conservation laws; Saltzman's Biomedical Engineering: Bridging Medicine and Technology builds the field outward from biology; Ritter and colleagues' Biomedical Engineering Principles is an introduction emphasising quantitative analysis and design; and Enderle's Introduction to Biomedical Engineering is a broad survey. Hobbie and Roth's Intermediate Physics for Medicine and Biology applies physics to physiology and medicine.

Read Wittrup and colleagues after one of the introductory texts and after courses in differential equations and molecular cell biology. It is complementary to Hobbie and Roth: that book is organised around physics, this one around molecular and cellular models.

How to Use This Book

The book suits advanced undergraduates and graduate students in chemical engineering and bioengineering, and was developed for classes the authors teach at MIT and the University of Minnesota. Calculus, differential equations, and introductory biology and chemistry are the sensible preparation.

A practical plan:

• Core: Chapters 1 to 4, which establish rate processes, binding and enzyme kinetics.
• Next: Chapter 5 (gene expression and trafficking) and Chapter 6 (network dynamics) for cell-level behaviour.
• By interest: Chapter 7 (growth) for bioprocess and population work, Chapter 8 (coupled transport and reaction) for drug delivery and tissue penetration, and Chapter 9 (stochastic processes) for single-cell variability.

Read the case studies alongside the text, with the original papers where possible, and work problems after each chapter; the problems and the nonlinear least-squares section are where the methods become usable.