Lecture 3: Dr. Jin Seob Kim

How do Keratin Intermediate Filaments self-assemble?

   Skin epidermal layers [2]

Intermediate filaments (IFs) provide structural and mechanical support vitally important to maintenance of cell and tissue integrity under stress. In vitro studies established that IFs must be crosslinked into a network in order to generate the elasticity and mechanical properties consistent with their mechanical support role in living cells. Accordingly, keratin IFs are typically organized into large bundles in epithelial surface. Skin epithelial cells express type I and type II IF genes, whose protein products copolymerize to form 10-nm-wide IFs in their cytoplasm. Experimentally, various types of keratin IFs are able to self-organize into crosslinked networks at subphysiological concentrations. For IFs comprised of keratin proteins 5 and 14 (K5, K14), found in basal keratinocytes of epidermis, bundling can be self-driven through interactions between K14's carboxy-terminal tail domain and two regions in the central α-helical rod domain of K5. 

Mechanisms of keratin filament bundling in basal keratinocytes of epidermis.
Ultrastructural examination shows that keratin filaments are abundant and show a
loosely bundled organization in basal layer keratinocytes of epidermis [3].

A number of fundamental questions remain about the pathway through which the keratin IF surface can promote the crosslinked network formation. In their work, Jin Seob Kim, Chang-Hun Lee and Pierre Coulombe from Johns Hopkins exploit theoretical principles and computational modeling to investigate how IF crosslinking happens. In their simple model, keratin IFs are treated as rigid rods to apply Brownian dynamics simulation. The authors' findings suggest that long-range interactions between IFs are required to initiate the formation of bundle-like configurations, while tail domain-mediated binding events act to stabilize them. The simple model explains the differences observed in the mechanical properties of wild-type versus disease-causing, defective IF networks. This effort extends the notion that the structural support function of keratin IFs necessitates a combination of intrinsic and extrinsic determinants, and makes specific predictions about the mechanisms involved in the formation of crosslinked keratin networks in vivo.

Theoretical time evolution of bundle formation [1]. 

Jin Seob's Article:

[1] Kim, Jin Seob, Chang-Hun Lee, and Pierre A. Coulombe. "Modeling the self-organization property of keratin intermediate filaments." Biophysical journal 99.9 (2010): 2748-2756.

References:

[2] Matsusaki, Michiya, et al. "Development of full‐thickness human skin equivalents with blood and lymph‐like capillary networks by cell coating technology." Journal of Biomedical Materials Research Part A 103.10 (2015): 3386-3396.

[3] Lee, Chang-Hun, and Pierre A. Coulombe. "Self-organization of keratin intermediate filaments into cross-linked networks." The Journal of cell biology 186.3 (2009): 409-421.

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Dr. Jin Seob Kim received a B.A. degree and M.S. degree in mechanical engineering from Seoul National University. After his master’s degree, he worked as a research engineer at SAMSUNG Electronics. In 2006, he received his Ph.D. degree in mechanical engineering at the Johns Hopkins University under the supervision of Dr. Gregory S. Chirikjian. After graduation, he worked as a postdoctoral fellow under the supervision of Drs. Sean Sun and Pierre Coulombe in the projects on computational cell morphology, cytoskeletal filaments, and skin homeostasis. Currently, he is an assistant research professor in the department of mechanical engineering at the Johns Hopkins University.

Dr. Kim’s research interests lie in mathematical modeling and simulation in the broad areas ranging from biology (molecular to cellular biology, systems biology and mechanobiology) and engineering (robotics and dynamics). 

Dr. Kim has published highly cited 9 first author papers and co-authored 4 papers in peer reviewed international journals. Also he has published 4 peer-reviewed papers in highly cited international conferences on robotics and computational biology.

Lecture 2: Nash Rochman (Sean Sun Lab)

To Grow is Not Enough

E. coli cell cycle duration distributions measured
at constant nutrient conditions. [1]

The mantra, “Survival of the Fittest,” coined by Spencer and popularized by Darwin himself, pervades every corner of biology. Fitness is usually defined to be the “birth-rate” or the rate at which new individuals are added to the population. Cooperative and multicellular systems may require a more complicated definition; but often even these phenomena are shown to derive from the maximization of total sustainable single cell number. In the case of non-cooperative, single cell species (e.g. bacteria at low cell density), fitness as birth-rate is accepted. For such a population during exponential growth, the number of cells in an ensemble can be well described as a function of time if we know the initial number N0, and the cell cycle duration τ, yielding N(t) = N0 exp(ln(2)t/τ). In this way the constant r = ln(2)/τ, often labeled the“growth-rate”, is used to measure fitness - the larger r and the faster an organism grows, the fitter it is.

Quantitative single cell measurements have shown that cell cycle duration (CCD, the time between cell divisions) for diverse cell types is a noisy variable. The underlying distribution of CCD is mean scalable with a universal shape for many cell types in a variety of environments. In their recent article, Nash Rochman and Sean Sun from Johns Hopkins mechanical engineering department have developed a phenomenological model for the regulation of cellular division time distributions determining both bulk growth rate and ensemble fluctuations. In this model, they propose a cellular ‘‘fitness’’ function which incorporates not only growth rate, which is maximized when fluctuations are minimized, but also ensemble response time to environmental stimulus which decreases for increasing fluctuations. Experimental single cell division data is collected on a population of isogenic cells subjected to varying environmental stimuli and compared to the model. The authors then have shown through both experiment and theory that increasing the amount of noise in the regulation of the cell cycle negatively impacts the growth rate, but positively correlates with improved cellular response to fluctuating environments. These results suggest that even non-cooperative cells in exponential growth phase do not optimize fitness through growth rate alone, but also optimize adaptability to changing conditions. In a manner similar to genetic evolution, increasing the noise in biochemical processes correlates with improved response of the system to environmental changes.

Nash's theory compared with eight step environmental change experiments. The experimental distributions are displayed using colors with highest probability in red and lowest probability in blue. The black lines are the model predictions for the average. [1]

Nash’s Article:

[1]: Rochman, Nash, Fangwei Si, and Sean X. Sun. "To Grow is Not Enough: Impact of Noise on Cell Environmental Response and Fitness." arXiv preprint arXiv:1603.01579 (2016).

Good reads on the subject:

P1: Hashimoto, Mikihiro, et al. "Noise-driven growth rate gain in clonal cellular populations." Proceedings of the National Academy of Sciences (2016): 201519412.

P2: Powell, E. O. "Growth rate and generation time of bacteria, with special reference to continuous culture." Microbiology 15.3 (1956): 492-511.

P3: Stukalin, Evgeny B., et al. "Age-dependent stochastic models for understanding population fluctuations in continuously cultured cells." Journal of The Royal Society Interface 10.85 (2013): 20130325.

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Nash Rochman studied chemical physics and mathematics in college (started at Bard College at Simon’s Rock and transferred to Brown) taking a particular interest in evolutionary dynamics which brought him to the ChemBE department here at Hopkins for his PhD. With his advisor Sean Sun (MechE), he has become engaged in a variety of problems motivated by exciting analytical predictions that also provide the potential for convincing experimental verification. When not in the office/lab, he likes to play and compose music – playing mostly jazz (trumpet) and writing mostly concert music.