Annual Review of Biomedical Engineering - Volume 17, 2015

Microfluidic cell-separation technologies have been studied for almost two decades, but the limited throughput has restricted their impact and range of application. Recent advances in microfluidics enable high-throughput cell sorting and separation, and this has led to various novel diagnostic and therapeutic applications that previously had been impossible to implement using microfluidics technologies. In this review, we focus on recent progress made in engineering large-volume microfluidic cell-sorting methods and the new applications enabled by them.

Traditionally, cell analysis has focused on using molecular biomarkers for basic research, cell preparation, and clinical diagnostics; however, new microtechnologies are enabling evaluation of the mechanical properties of cells at throughputs that make them amenable to widespread use. We review the current understanding of how the mechanical characteristics of cells relate to underlying molecular and architectural changes, describe how these changes evolve with cell-state and disease processes, and propose promising biomedical applications that will be facilitated by the increased throughput of mechanical testing: from diagnosing cancer and monitoring immune states to preparing cells for regenerative medicine. We provide background about techniques that laid the groundwork for the quantitative understanding of cell mechanics and discuss current efforts to develop robust techniques for rapid analysis that aim to implement mechanophenotyping as a routine tool in biomedicine. Looking forward, we describe additional milestones that will facilitate broad adoption, as well as new directions not only in mechanically assessing cells but also in perturbing them to passively engineer cell state.

In a range of human trials, viral vectors have emerged as safe and effective delivery vehicles for clinical gene therapy, particularly for monogenic recessive disorders, but there has also been early work on some idiopathic diseases. These successes have been enabled by research and development efforts focusing on vectors that combine low genotoxicity and immunogenicity with highly efficient delivery, including vehicles based on adeno-associated virus and lentivirus, which are increasingly enabling clinical success. However, numerous delivery challenges must be overcome to extend this success to many diseases; these challenges include developing techniques to evade preexisting immunity, to ensure more efficient transduction of therapeutically relevant cell types, to target delivery, and to ensure genomic maintenance. Fortunately, vector-engineering efforts are demonstrating promise in the development of next-generation gene therapy vectors that can overcome these barriers. This review highlights key historical trends in clinical gene therapy, the recent clinical successes of viral-based gene therapy, and current research that may enable future clinical application.

Digital microfluidics (DMF) is a droplet-based liquid-handling technology that has recently become popular for cell culture and analysis. In DMF, picoliter- to microliter-sized droplets are manipulated on a planar surface using electric fields, thus enabling software-reconfigurable operations on individual droplets, such as move, merge, split, and dispense from reservoirs. Using this technique, multistep cell-based processes can be carried out using simple and compact instrumentation, making DMF an attractive platform for eventual integration into routine biology workflows. In this review, we summarize the state-of-the-art in DMF cell culture, and describe design considerations, types of DMF cell culture, and cell-based applications of DMF.

Aging is a complex, multifaceted process that induces a myriad of physiological changes over an extended period of time. Aging is accompanied by major biochemical and biomechanical changes at macroscopic and microscopic length scales that affect not only tissues and organs but also cells and subcellular organelles. These changes include transcriptional and epigenetic modifications; changes in energy production within mitochondria; and alterations in the overall mechanics of cells, their nuclei, and their surrounding extracellular matrix. In addition, aging influences the ability of cells to sense changes in extracellular-matrix compliance (mechanosensation) and to transduce these changes into biochemical signals (mechanotransduction). Moreover, following a complex positive-feedback loop, aging is accompanied by changes in the composition and structure of the extracellular matrix, resulting in changes in the mechanics of connective tissues in older individuals. Consequently, these progressive dysfunctions facilitate many human pathologies and deficits that are associated with aging, including cardiovascular, musculoskeletal, and neurodegenerative disorders and diseases. Here, we critically review recent work highlighting some of the primary biophysical changes occurring in cells and tissues that accompany the aging process.

Cell signaling pathways control cells' responses to their environment through an intricate network of proteins and small molecules partitioned by intracellular structures, such as the cytoskeleton and nucleus. Our understanding of these pathways has been revised recently with the advent of more advanced experimental techniques; no longer are signaling pathways viewed as linear cascades of information flowing from membrane-bound receptors to the nucleus. Instead, such pathways must be understood in the context of networks, and studying such networks requires an integration of computational and experimental approaches. This understanding is becoming more important in designing novel therapies for diseases such as cancer. Using the MAPK (mitogen-activated protein kinase) and PI3K (class I phosphoinositide-3′ kinase) pathways as case studies of cellular signaling, we give an overview of these pathways and their functions. We then describe, using a number of case studies, how computational modeling has aided in understanding these pathways' deregulation in cancer, and how such understanding can be used to optimally tailor current therapies or help design new therapies against cancer.

Biosensors first appeared several decades ago to address the need for monitoring physiological parameters such as oxygen or glucose in biological fluids such as blood. More recently, a new wave of biosensors has emerged in order to provide more nuanced and granular information about the composition and function of living cells. Such biosensors exist at the confluence of technology and medicine and often strive to connect cell phenotype or function to physiological or pathophysiological processes. Our review aims to describe some of the key technological aspects of biosensors being developed for cell analysis. The technological aspects covered in our review include biorecognition elements used for biosensor construction, methods for integrating cells with biosensors, approaches to single-cell analysis, and the use of nanostructured biosensors for cell analysis. Our hope is that the spectrum of possibilities for cell analysis described in this review may pique the interest of biomedical scientists and engineers and may spur new collaborations in the area of using biosensors for cell analysis.

The use of monoclonal antibodies as therapeutics requires optimizing several of their key attributes. These include binding affinity and specificity, folding stability, solubility, pharmacokinetics, effector functions, and compatibility with the attachment of additional antibody domains (bispecific antibodies) and cytotoxic drugs (antibody–drug conjugates). Addressing these and other challenges requires the use of systematic design methods that complement powerful immunization and in vitro screening methods. We review advances in designing the binding loops, scaffolds, domain interfaces, constant regions, post-translational and chemical modifications, and bispecific architectures of antibodies and fragments thereof to improve their bioactivity. We also highlight unmet challenges in antibody design that must be overcome to generate potent antibody therapeutics.

Although skeletal muscle is one of the most regenerative organs in our body, various genetic defects, alterations in extrinsic signaling, or substantial tissue damage can impair muscle function and the capacity for self-repair. The diversity and complexity of muscle disorders have attracted much interest from both cell biologists and, more recently, bioengineers, leading to concentrated efforts to better understand muscle pathology and develop more efficient therapies. This review describes the biological underpinnings of muscle development, repair, and disease, and discusses recent bioengineering efforts to design and control myomimetic environments, both to study muscle biology and function and to aid in the development of new drug, cell, and gene therapies for muscle disorders. The synergy between engineering-aided biological discovery and biology-inspired engineering solutions will be the path forward for translating laboratory results into clinical practice.

In nature, nanometer-scale molecular motors are used to generate force within cells for diverse processes from transcription and transport to muscle contraction. This adaptability and scalability across wide temporal, spatial, and force regimes have spurred the development of biological soft robotic systems that seek to mimic and extend these capabilities. This review describes how molecular motors are hierarchically organized into larger-scale structures in order to provide a basic understanding of how these systems work in nature and the complexity and functionality we hope to replicate in biological soft robotics. These span the subcellular scale to macroscale, and this article focuses on the integration of biological components with synthetic materials, coupled with bioinspired robotic design. Key examples include nanoscale molecular motor-powered actuators, microscale bacteria-controlled devices, and macroscale muscle-powered robots that grasp, walk, and swim. Finally, the current challenges and future opportunities in the field are addressed.

Fast and reliable diagnoses are invaluable in clinical care. Samples (e.g., blood, urine, and saliva) are collected and analyzed for various biomarkers to quickly and sensitively assess disease progression, monitor response to treatment, and determine a patient's prognosis. Processing conventional samples entails many manual time-consuming steps. Consequently, clinical specimens must be processed by skilled technicians before antigens or nucleic acids are detected, and these are often present at dilute concentrations. Recently, several automated microchip technologies have been developed that potentially offer many advantages over traditional bench-top extraction methods. The smaller length scales and more refined transport mechanisms that characterize these microfluidic devices enable faster and more efficient biomarker enrichment and extraction. Additionally, they can be designed to perform multiple tests or experimental steps on one integrated, automated platform. This review explores the current research on microfluidic methods of sample preparation that are designed to aid diagnosis, and covers a broad spectrum of extraction techniques and designs for various types of samples and analytes.

Mechanical stimuli are known to be potent regulators of the form and function of cells and organisms. Although biological regulation has classically been understood in terms of principles from solution biochemistry, advancements in many fields have led to the development of a suite of techniques that are able to reveal the interplay between mechanical loading and changes in the biochemical properties of proteins in systems ranging from single molecules to living organisms. Here, we review these techniques and highlight the emergence of a new molecular-scale understanding of the mechanisms mediating the detection and response of cells to mechanical stimuli, a process termed mechanotransduction. Specifically, we focus on the role of subcellular adhesion structures in sensing the stiffness of the surrounding environment because this process is pertinent to applications in tissue engineering as well the onset of several mechanosensitive disease states, including cancer.

Strategies to enhance, suppress, or qualitatively shape the immune response are of importance for diverse biomedical applications, such as the development of new vaccines, treatments for autoimmune diseases and allergies, strategies for regenerative medicine, and immunotherapies for cancer. However, the intricate cellular and molecular signals regulating the immune system are major hurdles to predictably manipulating the immune response and developing safe and effective therapies. To meet this challenge, biomaterials are being developed that control how, where, and when immune cells are stimulated in vivo, and that can finely control their differentiation in vitro. We review recent advances in the field of biomaterials for immunomodulation, focusing particularly on designing biomaterials to provide controlled immunostimulation, targeting drugs and vaccines to lymphoid organs, and serving as scaffolds to organize immune cells and emulate lymphoid tissues. These ongoing efforts highlight the many ways in which biomaterials can be brought to bear to engineer the immune system.

Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation.

Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.

Advancements in coherent Raman scattering (CRS) microscopy have enabled label-free visualization and analysis of functional, endogenous biomolecules in living systems. When compared with spontaneous Raman microscopy, a key advantage of CRS microscopy is the dramatic improvement in imaging speed, which gives rise to real-time vibrational imaging of live biological samples. Using molecular vibrational signatures, recently developed hyperspectral CRS microscopy has improved the readout of chemical information available from CRS images. In this article, we review recent achievements in CRS microscopy, focusing on the theory of the CRS signal-to-noise ratio, imaging speed, technical developments, and applications of CRS imaging in bioscience and clinical settings. In addition, we present possible future directions that the use of this technology may take.

The Computational Anatomy project is the morphome-scale study of shape and form, which we model as an orbit under diffeomorphic group action. Metric comparison calculates the geodesic length of the diffeomorphic flow connecting one form to another. Geodesic connection provides a positioning system for coordinatizing the forms and positioning their associated functional information. This article reviews progress since the Euler-Lagrange characterization of the geodesics a decade ago. Geodesic positioning is posed as a series of problems in Hamiltonian control, which emphasize the key reduction from the Eulerian momentum with dimension of the flow of the group, to the parametric coordinates appropriate to the dimension of the submanifolds being positioned. The Hamiltonian viewpoint provides important extensions of the core setting to new, object-informed positioning systems. Several submanifold mapping problems are discussed as they apply to metamorphosis, multiple shape spaces, and longitudinal time series studies of growth and atrophy via shape splines.