Mechanomics Approaches to Understand Cell Behavior in Context of Tissue Neogenesis, During Prenatal Development and Postnatal Healing

Putra, Vina D. L.; Song, Min Jae; McBride‐Gagyi, Sarah; Chang, Hong‐Shiu; Poole, Kate; Whan, Renée; Dean, David; Sansalone, V.; Tate, Melissa L. Knothe

doi:10.3389/fcell.2019.00354

Cited by 8 publications

(9 citation statements)

References 37 publications

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“…Broadly speaking, mechanomics is a study of omics data within the context of mechanobiology. So far, this term was used with regard to changes in omics profiles in response to a mechanical stimuli such as shear flow, tensile stretch, or mechanical compression [33][34][35] , or to collectively name all of the mechanical forces acting on or within cells [36][37][38][39][40] . However, it can also be used to address omics changes related to changes in the mechanical properties of cells 41,42 -a context much closer to our study.…”

Section: Introductionmentioning

confidence: 99%

De novo identification of universal cell mechanics gene signatures

Urbanska

Winzi

et al. 2021

Preprint

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Mechanical proprieties determine many cellular functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors governing cell mechanical phenotype is therefore a subject of great interest. Here we present a mechanomics approach for establishing links between mechanical phenotype changes and the genes involved in driving them. We employ a machine learning-based discriminative network analysis method termed PC-corr to associate cell mechanical states, measured by real-time deformability cytometry (RT-DC), with large-scale transcriptome datasets ranging from stem cell development to cancer progression, and originating from different murine and human tissues. By intersecting the discriminative networks inferred from two selected datasets, we identify a conserved module of five genes with putative roles in the regulation of cell mechanics. We validate the power of the individual genes to discriminate between soft and stiff cell states in silico, and demonstrate experimentally that the top scoring gene, CAV1, changes the mechanical phenotype of cells when silenced or overexpressed. The data-driven approach presented here has the power of de novo identification of genes involved in cell mechanics regulation and paves the way towards engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions.

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Section: Introductionmentioning

confidence: 99%

De novo identification of universal cell mechanics gene signatures

Urbanska

Winzi

et al. 2021

Preprint

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“…Throughout prenatal development as well as during postnatal healing, which repeats prenatal development processes, cells interconvert between epithelial and mesenchymal states (EMTs and EMTs, as per above), enabling the formation of complex geometries, tissue architectures, and organ systems ( Figures 1A,B ; Morali et al, 2004 ; Putra et al, 2020 ). The process is so ubiquitous that the formation of deleterious tissues such as cancerous tumors and metastasis of circulating tumor cells follow analogous paradigms ( Jolly et al, 2017 ).…”

Section: Tissues Cells Weave and Their Smart Propertiesmentioning

confidence: 99%

“…“This representation recovers scaling relations E ∼λ max -2, for elastomeric materials with λ max ≫ 1, and E ∼ε max -2, for hard materials with strain at break ε max = λ max -1 ≪ 1.” Panels (A,B) used with permission from Sheiko and Dobrynin (2019) and Vatankhah-Varnosfaderani et al (2017) . (C) Master Table of properties for materials created using MADAME and tested in tension, compared to textile and isotropic control materials , using data from Ng et al (2017a , b , c , 2019 , 2020 ).…”

Section: Microscopy-aided Design and Manufacture (Madame) Of Bio-inspmentioning

confidence: 99%

Advanced Design and Manufacture of Mechanoactive Materials Inspired by Skin, Bones, and Skin-on-Bones

Tate

2020

Front. Bioeng. Biotechnol.

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Life is mechanobiological. Natural living materials exhibit remarkable, emergent and smart properties under mechanical loading. Such materials are classified as mechanoactive , in contrast to electroactive polymers and materials that exhibit advanced properties when subjected to electrical stimulation. Cutting edge, multiscale imaging technologies have proven enabling for the elucidation of molecular to meso-scale structure and function of natural mechanoactive materials. Using Microscopy-Aided Design And ManufacturE, (MADAME) this perspective article describes mechanoactive properties of natural materials including skin-on-bones ( periosteum ) and bone itself. In so doing, it demonstrates the principle to emulate natural smart properties using recursive logic, the basis of many computer algorithms, and to design and manufacture mechanoactive materials and products using advanced manufacturing methods that also incorporate principles of recursive logic. In sum, the MADAME approach translates physically the computer science paradigm of recursion by implementing Jacquard textile methods, which themselves form a historical basis for computing machines, together with additive manufacturing methods including multidimensional printing, stereolithography, laser sintering, etc. These integrated methods provide a foundation and translational pathway for scaled-up manufacture of disruptive mechanoactive materials that will find use in fields as varied as medicine, safety, transport and sports, for internal (implants) and external (wearables) applications.

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“…The manuscript proposes a paradigm shifting approach to understand the cellular underpinnings of diseases as different as osteoarthritis and early onset dementia in bone and brain. We know as biologists that cells manufacture, remodel and adapt tissues throughout life ( Knothe Tate et al, 2016a ; Putra et al, 2019 ). The tissues render physically the collective cellular experience, reflected in architectures (bones) and memories (brain) which themselves exhibit emergent properties ( Knothe Tate, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience

Tate¹,

Srikantha

Wojek

et al. 2021

Front. Physiol.

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“Brainless” cells, the living constituents inhabiting all biological materials, exhibit remarkably smart, i.e., stimuli-responsive and adaptive, behavior. The emergent spatial and temporal patterns of adaptation, observed as changes in cellular connectivity and tissue remodeling by cells, underpin neuroplasticity, muscle memory, immunological imprinting, and sentience itself, in diverse physiological systems from brain to bone. Connectomics addresses the direct connectivity of cells and cells’ adaptation to dynamic environments through manufacture of extracellular matrix, forming tissues and architectures comprising interacting organs and systems of organisms. There is imperative to understand the physical renderings of cellular experience throughout life, from the time of emergence, to growth, adaptation and aging-associated degeneration of tissues. Here we address this need through development of technological approaches that incorporate cross length scale (nm to m) structural data, acquired via multibeam scanning electron microscopy, with machine learning and information transfer using network modeling approaches. This pilot case study uses cutting edge imaging methods for nano- to meso-scale study of cellular inhabitants within human hip tissue resected during the normal course of hip replacement surgery. We discuss the technical approach and workflow and identify the resulting opportunities as well as pitfalls to avoid, delineating a path for cellular connectomics studies in diverse tissue/organ environments and their interactions within organisms and across species. Finally, we discuss the implications of the outlined approach for neuromechanics and the control of physical behavior and neuromuscular training.

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Mechanomics Approaches to Understand Cell Behavior in Context of Tissue Neogenesis, During Prenatal Development and Postnatal Healing

Cited by 8 publications

References 37 publications

De novo identification of universal cell mechanics gene signatures

De novo identification of universal cell mechanics gene signatures

Advanced Design and Manufacture of Mechanoactive Materials Inspired by Skin, Bones, and Skin-on-Bones

Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience

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