IntroductionStudying plant-microbe interactions is one of the key elements in understanding the path to sustainable agricultural practices. These interactions play a crucial role in ensuring survival of healthy plants, soil and microbial communities. Many platforms have been developed over the years to isolate these highly complex interactions however, these are designed for small model plants. This creates a need for complementary devices for larger plants, such as sorghum.MethodsThis work introduces a novel platform, EcoFAB 3.0, which is designed to enable studying bioenergy plants such as sorghum for up to 4 weeks in a controlled sterile environment. Several other advantages of this platform such as dark root chambers and user-friendly assembly are also discussed in this work.Results and discussionEcoFAB 3.0 was found to replicate previous greenhouse and field observations when comparing an engineered sorghum line overproducing 4-hydroxybenzoic acid (4-HBA) and wildtype (variety BTx430). Consistent with greenhouse and field observations, it was found that the engineered line of sorghum grown in EcoFAB 3.0 had a higher 4-HBA content and a lower dry biomass.

Mass spectrometry (MS) enables detection of different chemical species with a very high specificity; however, it can be limited by its throughput. Integrating MS with microfluidics has a tremendous potential to improve throughput and accelerate biochemical research. In this work, we introduce Drop-NIMS, a combination of a passive droplet loading microfluidic device and a matrix-free MS laser desorption ionization technique called nanostructure-initiator mass spectrometry (NIMS). This platform combines different droplets at random to generate a combinatorial library of enzymatic reactions that are deposited directly on the NIMS surface without requiring additional sample handling. The enzyme reaction products are then detected with MS. Drop-NIMS was used to rapidly screen enzymatic reactions containing low (on the order of nL) volumes of glycoside reactants and glycoside hydrolase enzymes per reaction. MS "barcodes" (small compounds with unique masses) were added to the droplets to identify different combinations of substrates and enzymes created by the device. We assigned xylanase activities to several putative glycoside hydrolases, making them relevant to food and biofuel industrial applications. Overall, Drop-NIMS is simple to fabricate, assemble, and operate and it has potential to be used with many other small molecule metabolites.

Marginal zone B cells (MZB) participate in the early immune response to several pathogens. In this study, we show that in μMT mice infected with Leishmania donovani, CD8 T cells displayed a greater cytotoxic potential and generated more effector memory cells compared with infected wild type mice. The frequency of parasite-specific, IFN-γ(+) CD4 T cells was also increased in μMT mice. B cells were able to capture parasites, which was associated with upregulation of surface IgM and MyD88-dependent IL-10 production. Moreover, MZB presented parasite Ags to CD4 T cells in vitro. Depletion of MZB also enhanced T cell responses and led to a decrease in the parasite burden but did not alter the generation of effector memory T cells. Thus, MZB appear to suppress protective T cell responses during the early stages of L. donovani infection.

The introduction of microtechnology and microfluidic platforms for cell culture can dramatically enhance the pace of stem cell research. With the use of microfluidic-based techniques, extracellular microenvironments can be controlled in a precise manner, and their influence on various cellular behaviors can be studied. Microfluidic devices made of transparent materials allow real-time and high-throughput monitoring of cell functions and cell fate by using fluorescence microscopy and other optical techniques. This chapter gives a perspective on the considerable capability of microfluidic devices, which remain an underutilized technology for stern cell research. It provides stem cell researchers with a brief review of basic microtechnology and the application of microfluidics to stem cell research, as well as highlights to engineers the peculiarities of stem cell culture and experimental capabilities of microfluidics. In addition, it provides insights into creating integrated, modular, and easy-to-use microfluidic devices to perturb stem cells with biochemico/mechanical stimuli in a precise, controlled, combinatorial, and high-throughput fashion.

Recently, putative adult cardiac stems cells have been isolated and investigated in the laboratory and clinical settings. In spite of demonstrated repair potential, the utility of transplantation of these cells remains in doubt due to high cell mortality and low tissue integration. Here we demonstrate that the scalable (>1 cm2) nanostructured scaffold of biocompatible hydrogels can produce structurally aligned cardiac stem cell sheets, which mimic the aligned cardiophysiological architecture seen in normal heart tissue in vivo. Through in vitro characterization, we also demonstrate that topographically‐controlled cardiac stem cells grown on the scaffolds show significant increase in cell adhesion, migration, and proliferation compared to the control group. Furthermore, in vitro co‐culture of neonatal rat ventricular myocytes with lentivirally transduced cardiac stem cells expressing NCX promoter‐GFP exhibited enhanced cardiac differentiation on nanofabricated scaffolds. To test the therapeutic potential in vivo, we engrafted the monolayered cardiac stem cell patches onto the infarcted heart of adult rats. We found that engrafted GFP‐labelled cardiac stem cells migrated into and integrated with host cardiac tissue. This was evidenced by formation of stable gap junctions and expression of the cardiac specific marker Troponin I. There was a clear improvement in tissue repair as indicated by thicker infarct walls in those animals that received the stem cell graft. Overall, we argue that our method not only enables development of functional cardiac grafts, but also provides a novel therapeutic approach to promote cardiac regeneration and improve healing in a rat myocardial infarction model.

The advent of stem cell based therapies has brought regenerative medicine into an increased focus as a part of the modern medicine practice, with a potential to treat a myriad of intractable diseases in the future. Stem cells reside in a complex microenvironment presenting them with a multitude of potential cues that are chemical, physical, and mechanical in nature. Conventional techniques used for experiments involving stem cells can only poorly mimic the physiological context, and suffer from imprecise spatial and temporal control, low throughput, lack of scalability and reproducibility, and poor representation of the mechanical and physical cell microenvironment. Novel lab-on-a-chip platforms, on the other hand, can much better mimic the complexity of in vivo tissue milieu and provide a greater control of the parameter variation in a high throughput and scalable manner. This capability may be especially important for understanding the biology and cementing the clinical potential of stem cell based therapies. Here we review microfabrication- and microfluidics-based approaches to investigating the complex biology of stem cell responses to changes in the local microenvironment. In particular, we categorize each method based on the types of controlled inputs it can have on stem cells, including soluble biochemical factors, extracellular matrix interactions, homotypic and heterotypic cell-cell signaling, physical cues (e.g. oxygen tension, pH, temperature), and mechanical forces (e.g. shear, topography, rigidity). Finally, we outline the methods to perform large scale observations of stem cell phenotypes and high-throughput screening of cellular responses to a combination of stimuli, and many new emerging technologies that are becoming available specifically for stem cell applications.

In this report, we describe using ultraviolet (UV)-assisted capillary force lithography (CFL) to create a model substratum of anisotropic micro- and nanotopographic pattern arrays with variable local density for the analysis of cell–substratum interactions. A single cell adhesion substratum with the constant ridge width (1μm), and depth (400nm) and variable groove widths (1–9.1μm) allowed us to characterize the dependence of cellular responses, including cell shape, orientation, and migration, on the anisotropy and local density of the variable micro- and nanotopographic pattern. We found that fibroblasts adhering to the denser pattern areas aligned and elongated more strongly along the direction of ridges, vs. those on the sparser areas, exhibiting a biphasic dependence of the migration speed on the pattern density. In addition, cells responded to local variations in topography by altering morphology and migrating along the direction of grooves biased by the direction of pattern orientation (short term) and pattern density (long term), suggesting that single cells can sense the topography gradient. Molecular dynamic live cell imaging and immunocytochemical analysis of focal adhesions and actin cytoskeleton suggest that variable substratum topography can result in distinct types of cytoskeleton reorganization. We also demonstrate that fibroblasts cultured as monolayers on the same substratum retain most of the properties displayed by single cells. This result, in addition to demonstrating a more sophisticated method to study aspects of wound healing processes, strongly suggests that even in the presence of adhesive cell–cell interactions, the cues provided by the underlying substratum topography continue to exercise substantial influence on cell behavior. The described experimental platform might not only further our understanding of biomechanical regulation of cell–matrix interactions, but also contribute to bioengineering of devices with the optimally structured design of cell–material interface.

Recent evidence from different research areas has revealed a novel mechanism of cell-cell communication by spontaneous intercellular transfer of cellular components (ICT). Here we studied this phenomenon by co-culturing different cells that contain distinct levels of proteins or markers for the plasma membrane or cytoplasm. We found that a variety of transmembrane proteins are transferable between multiple cell types. Membrane lipids also show a high efficiency of intercellular transfer. Size-dependent cytoplasmic transfer allows exchange of cytoplasmic macromolecules up to 40 kDa between somatic cells, and up to 2000 kDa between uncommitted human precursor cells and human umbilical vein endothelial cells. Protein transfer, lipid transfer and cytoplasmic component transfer can occur simultaneously and all require direct cell-cell contact. Analyses of the properties of ICT, together with a close examination of cell-cell interactions, suggest that the spontaneous ICT of different cellular components might have a common underlying process: transient local membrane fusions formed when neighboring cells undergo close cell-cell contact.

Ischemia induces the production of angiogenic cytokines and the homing of bone-marrow-derived angiogenic cells (BMDACs), but these adaptive responses become impaired with aging because of reduced expression of hypoxia-inducible factor (HIF)-1α. In this study, we analyzed the effect of augmenting HIF-1α levels in ischemic limb by intramuscular injection of AdCA5, an adenovirus encoding a constitutively active form of HIF-1α, and intravenous administration of BMDACs that were cultured in the presence of the prolyl-4-hydroxylase inhibitor dimethyloxalylglycine (DMOG) to induce HIF-1 expression. The combined therapy increased perfusion, motor function, and limb salvage in old mice subjected to femoral artery ligation. Homing of BMDACs to the ischemic limb was dramatically enhanced by intramuscular AdCA5 administration. DMOG treatment of BMDACs increased cell surface expression of β2 integrins, which mediated increased adherence of BMDACs to endothelial cells. The effect of DMOG was abolished by coadministration of the HIF-1 inhibitor digoxin or by preincubation with a β2 integrin-blocking antibody. Transduction of BMDACs with lentivirus LvCA5 induced effects similar to DMOG treatment. Thus, HIF-1α gene therapy increases homing of BMDACs to ischemic muscle, whereas HIF-1 induction in BMDACs enhances their adhesion to vascular endothelium, leading to synergistic effects of combined therapy on tissue perfusion.

Background: Prediction of function of proteins on the basis of structure and vice versa is a partially solved problem, largely in the domain of biophysics and biochemistry. This underlies the need of computational and bioinformatics approach to solve the problem. Large and organized latent knowledge on protein classification exists in the form of independently created protein classification databases. By creating probabilistic maps between classes of structural classification databases (e.g. SCOP [1]) and classes of functional classification databases (e.g. PROSITE [2]), structure and function of proteins could be probabilistically related.Results: We demonstrate that PROSITE and SCOP have significant semantic overlap, in spite of independent classification schemes. By training classifiers of SCOP using classes of PROSITE as attributes and vice versa, accuracy of Support Vector Machine classifiers for both SCOP and PROSITE was improved. Novel attributes, 2-D elastic profiles and Blocks were used to improve time complexity and accuracy. Many relationships were extracted between classes of SCOP and PROSITE using decision trees.Conclusion: We demonstrate that presented approach can discover new probabilistic relationships between classes of different taxonomies and render a more accurate classification. Extensive mappings between existing protein classification databases can be created to link the large amount of organized data. Probabilistic maps were created between classes of SCOP and PROSITE allowing predictions of structure using function, and vice versa. In our experiments, we also found that functions are indeed more strongly related to structure than are structure to functions.

BACKGROUND:The chemical property and biological function of a protein is a direct consequence of its primary structure. Several algorithms have been developed which determine alignment and similarity of primary protein sequences. However, character based similarity cannot provide insight into the structural aspects of a protein. We present a method based on spectral similarity to compare subsequences of amino acids that behave similarly but are not aligned well by considering amino acids as mere characters. This approach finds a similarity score between sequences based on any given attribute, like hydrophobicity of amino acids, on the basis of spectral information after partial conversion to the frequency domain.RESULTS:Distance matrices of various branches of the human kinome, that is the full complement of human kinases, were developed that matched the phylogenetic tree of the human kinome establishing the efficacy of the global alignment of the algorithm. PKCd and PKCe kinases share close biological properties and structural similarities but do not give high scores with character based alignments. Detailed comparison established close similarities between subsequences that do not have any significant character identity. We compared their known 3D structures to establish that the algorithm is able to pick subsequences that are not considered similar by character based matching algorithms but share structural similarities. Similarly many subsequences with low character identity were picked between xyna-theau and xyna-clotm F/10 xylanases. Comparison of 3D structures of the subsequences confirmed the claim of similarity in structure.CONCLUSION:An algorithm is developed which is inspired by successful application of spectral similarity applied to music sequences. The method captures subsequences that do not align by traditional character based alignment tools but give rise to similar secondary and tertiary structures. The Spectral Similarity Score (SSS) is an extension to the conventional similarity methods and results indicate that it holds a strong potential for analysis of various biological sequences and structural variations in proteins.