Total and viable microbial cell counts are increasingly important for applications including live biotherapeutic products, food safety, and probiotics. In microbiology, cells are quantified using methods such as colony forming unit (CFU), flow cytometry, and polymerase chain reaction (PCR), but different methods measure different aspects of the cells (measurands), and results may not be directly comparable across methods. In the absence of a ground-truth reference material for cell count, one cannot quantify the accuracy of any cell counting method, which limits method performance assessments and comparisons. Herein, a modified analysis of cell counting methods based on the ISO 20391-2:2019 standard was developed and demonstrated for microbial cell samples diluted over a log-scale range of concentrations. Escherichia coli samples ranging in concentration from ~5 x 105 cells/mL to 2 x 107 cells/mL were quantified using CFU, Coulter principle, fluorescence flow cytometry, and impedance flow cytometry. Quality metrics modified from the ISO standard were calculated for each method and shown to be repeatable across replicate experiments. The quality metrics illustrate large differences in proportionality and variability across methods, with total cell counts in good agreement and viable cell count having more variability. As the ISO standard is meant to guide fit-for-purpose method selection, interpretation of the results and quality metrics can drive method choice and optimization. The framework introduced here will help researchers select fit-for-purpose counting methods for quantification of microbial total and viable cells across a range of applications.

This work explored the role of natural transformation – a mechanism by which bacteria uptake and express extracellular genes - in driving antibiotic resistance propagation in the human gut microbiome. The model extracellular antibiotic resistance gene (eARG) - a plasmid containing a kanamycin resistance (kanR) gene and a green fluorescence protein (GFP) gene - was dosed into pooled and homogenized human stool and incubated anaerobically. Cellular uptake of the eARG was assessed via droplet digital PCR, the expression of newly acquired genes was assessed by culturing on selective media and fluorescent microscopy, newly resistant isolates were identified by long-read Nanopore sequencing and the impacts on the taxonomy of the gut microbiome was assessed using shotgun Illumina sequencing. Significant gene uptake of both kanR and GFP was quantified in gut microbes, and extent of gene accumulation correlated with background kanamycin levels. Gut microbes dosed with background kanamycin expressed kanamycin resistance acquired by the eARG (as quantified by CFU on kanamycin-containing media). Newly resistant isolates, identified as Enterococcus faecium by long-read sequencing, also expressed green fluorescence acquired from the eARG. Though compositional changes of the kanamycin-resistant subpopulation were observed in the gut microbiome in response to eARG and antibiotic exposure, these changes were not reproducible among replicates and trends in taxonomy due to transformation could not be identified. This comprehensive analysis therefore establishes the significant propagation of antibiotic resistance within the human gut microbiome due to eARG exposure, while evaluating the utility of various measurements in characterizing transformation in a complex microbial community.

Typical studies of gastral toxicity of nanoparticles are conducted using radio labeling. This tends to be quite expensive and difficult owing to both the required protocols for working with these materials and also the expense of both the chemical reagents and dedicated instrumentation. A possible alternative is fluorescence labeling. Fluorescence is just as sensitive as scintillation, given that scintillation is itself a fluorescence measurement and subject to the same limitations. However, most fluorophores are sensitive to changes in pH and hydrolysis reactions present in most mammalian digestive tracts. Here we report the synthesis of a new pH insensitive and hydrolitically stable fluorophore, 10-(4-(3,5-dichlorophenoxy)phenyl)-2,8-diethyl-5,5-difluoro-1,3,7,9-tetramethyl-5 H-4l4,5l4-dipyrrolo[1,2-c:2',1'-f][1,3,2]diazaborinine (mDTEB). This fluorophore is based on the high quantum yield Boron-dipyrromethene (BODIPY) fluorescent center and is equipped with a reactive handle for convenient attachment to polysaccharides. We validate its effectiveness by labelling cellulose nano fibers (CNFs) to produce homogeneously labelled bright nanofibrils for toxicity studies.

In the field of tissue engineering, 3D scaffolds and cells are often combined to yield constructs that are used as therapeutics to repair or restore tissue function in patients. Viable cells are often required to achieve the intended mechanism of action for the therapy, where the live cells may build new tissue or may release factors that induce tissue regeneration. Thus, there is a need to reliably measure cell viability in 3D scaffolds as a quality attribute of a tissue-engineered medical product. Here, we developed a noninvasive, label-free, 3D optical coherence tomography (OCT) method to rapidly (2.5 min) image large sample volumes (1 mm3 ) to assess cell viability and distribution within scaffolds. OCT imaging was assessed using a model scaffold-cell system consisting of a polysaccharide-based hydrogel seeded with human Jurkat cells. Four test systems were used: hydrogel seeded with live cells, hydrogel seeded with heat-shocked or fixed dead cells and hydrogel without any cells. Time series OCT images demonstrated changes in the time-dependent speckle patterns due to refractive index (RI) variations within live cells that were not observed for pure hydrogel samples or hydrogels with dead cells. The changes in speckle patterns were used to generate live-cell contrast by image subtraction. In this way, objects with large changes in RI were binned as live cells. Using this approach, on average, OCT imaging measurements counted 326 ± 52 live cells per 0.288 mm3 for hydrogels that were seeded with 288 live cells (as determined by the acridine orange-propidium iodide cell counting method prior to seeding cells in gels). Considering the substantial uncertainties in fabricating the scaffold-cell constructs, such as the error from pipetting and counting cells, a 13% difference in the live-cell count is reasonable. Additionally, the 3D distribution of live cells was mapped within a hydrogel scaffold to assess the uniformity of their distribution across the volume. Our results demonstrate a real-time, noninvasive method to rapidly assess the spatial distribution of live cells within a 3D scaffold that could be useful for assessing tissue-engineered medical products.

Nanofiber scaffolds can induce osteogenic differentiation and cell morphology alterations of human bone marrow stromal cells (hBMSCs) without introduction of chemical cues. In this study, we investigate the predictive power of day 1 cell morphology, quantified by a machine learning based method, as an indicator of osteogenic differentiation modulated by nanofiber density. Nanofiber scaffolds are fabricated via electrospinning. Microscopy, quantitative image processing and clustering analysis are used to systematically quantify scaffold properties as a function of fiber density. hBMSC osteogenic differentiation potential is evaluated after 14 days using osteogenic marker gene expression and after 50 days using calcium mineralization, showing enhanced osteogenic differentiation with an increase in nanofiber density. Cell morphology measurements at day 1 successfully predict differentiation potential when analyzed with the support vector machine (SVM)/supercell tools previously developed and trained on cells from a different donor. A correlation is observed between differentiation potential and cell morphology, demonstrating sensitivity of the morphology measurement to varying degrees of differentiation potential. To further understand how nanofiber density determines hBMSC morphology, both full 3-D morphology measurements as well as other measurements of the 2-D projected morphology are investigated in this study. To achieve predictive power on hBMSC osteogenic differentiation, at least two morphology metrics need to be considered together for each cell, with the majority of metric pairs including one 3-D morphology metric. Analysis of the local nanofiber structure surrounding each cell reveals a correlation with single-cell morphology and indicates that the osteogenic differentiation phenotype may be predictive at the single-cell level.

This study experimentally substantiates that the micromechanical compatibility between cell and substrate is essential for cells to achieve energetically favorable mechano-transduction that directs phenotypic transitions. The argument for this compatibility is based on a thermodynamic model that suggests that the response of cells to their substrate mechanical environment is a consequence of the interchange between forms of energy governing the cell-substrate interaction. Experimental validation for the model has been carried out by investigating the osteogenic differentiation of dental follicle stem cells (DFSCs) seeded on electrospun fibrous scaffolds. Electrospinning of blends containing polycaprolactone (PCL) and silk fibroin (SF) with varying composition of cellulose nanocrystals (CNCs) resulted in three- dimensional (3D) fibrous scaffolds with bimodal distribution of fiber diameter, which provides both macroscopically stiff and microscopically compliant scaffolds for cells without affecting the surface chemical functionality of scaffolds. Atomic force microscopy (AFM) with a colloidal probe and single-cell force spectroscopy were used to characterize cell stiffness and scaffold stiffness on the cellular level, as well as cell-scaffold adhesive interaction (chemical functionality). This study has successfully varied scaffold mechanical properties without affecting their surface chemistry. In vitro tests indicate that the micromechanical compatibility between cells and scaffolds has been significantly correlated with mechanosensitive gene expression markers and osteogenic differentiation markers of DFSCs. The agreement between experimental observations and the thermodynamic model affirms that the cellular response to the mechanical environment, though biological in nature, follows the laws of the energy interchange to achieve its self-regulating behavior. More importantly, this study provides systematic evidence, through extensive and rigorous experimental studies, for the first time that rationalizes that micromechanical compatibility is indeed important to the efficacy of regenerative medicine.

We aim to develop a quantitative viability method that distinguishes individual quiescent from dead cells and is measured in time (ns) as a referenceable, comparable quantity. We demonstrate that fluorescence lifetime imaging of an anionic, fluorescent membrane voltage probe fulfills these requirements for Streptococcus mutans. A random forest machine-learning model assesses whether individual S. mutans can be correctly classified into their original populations: stationary phase (quiescent), heat killed and inactivated via chemical fixation. We compare the results to intensity using three models: lifetime variables (τ1 , τ2 and p1 ), phasor variables (G, S) or all five variables, with the five variable models having the most accurate classification. This initial work affirms the potential for using fluorescence lifetime of a membrane voltage probe as a viability marker for quiescent bacteria, and future efforts on other bacterial species and fluorophores will help refine this approach.

One common tissue engineering approach for regenerating or replacing damaged tissues involves a porous polymeric scaffold. The scaffolds serve as the mechanical framework for cell attachment and growth, and generate an environment with features that span multiple-length scales to guide cell differentiation and tissue regeneration. Laser scanning confocal microscopy (LSCM) is a useful technique to evaluate cell adhesion and spatial distribution within a scaffold since it is designed to collect image slices through the sample thickness. This chapter discusses the methods to evaluate cell distribution in the scaffolds using LSCM. Cell distribution in 3D scaffolds was characterized using new methods developed for the LSCM. Scaffold porosity and pore size are important factors for cell proliferation and distribution in 3D. Porosity affects diffusion and is vital for nutrient distribution and waste removal. All methods utilized the imaging capabilities of the LSCM while also taking advantage of the low-scattering nature of the amorphous polymers.

Despite their great promise as fluorescent biological probes and sensors, the structure and dynamics of Ag complexes derived from single stranded DNA (ssDNA) are less understood than their double stranded counterparts. In this work, we seek new insights into the structure of single AgNssDNA clusters using analytical ultracentrifugation (AUC), nuclear magnetic resonance spectroscopy, infrared spectroscopy and molecular dynamics simulations (MD) of a fluorescent (AgNssDNA) 8+ nanocluster. The results suggest that the purified (AgNssDNA) 8+ nanocluster is a mixture of predominantly Ag15 and Ag16 species that prefer two distinct long-lived conformational states: one extended, the other approaching spherical. However, the ssDNA strands within these clusters are highly mobile. Ag(I) interacts preferentially with the nucleobase rather than the phosphate backbone, causing a restructuring of the DNA strand relative to the bare DNA. Infrared spectroscopy and MD simulations of (AgNssDNA) 8+ and model nucleic acid homopolymers suggest that Ag(I) has a higher affinity for cytosine over guanine bases, little interaction with adenine, and virtually none with thymine. Ag(I) shows a tendency to interact with cytosine N3 and O2 and guanine N7 and O6, opening the possibility for a Ag(I)-base bifurcated bond to act as a nanocluster nucleation and strand stabilizing site. This work provides valuable insight into nanocluster structure and dynamics which drive stability and optical properties, and additional studies using these types of characterization techniques are important for the rational design of single stranded AgDNA nanocluster sensors.

Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and multi-parametric definitions of cell morphology. To associate cell morphology with cell-material interactions, we developed a shape phenotyping framework based on support vector machines. A feature selection procedure was implemented to select the most significant combination of cell shape metrics to build classifiers with both accuracy and stability to identify and predict microenvironment-driven morphological differences in heterogeneous cell populations. The analysis was conducted at a multi-cell level, where a "supercell" method used average shape measurements of small groups of single cells to account for heterogeneous populations and microenvironment. A subsampling validation algorithm revealed the range of supercell sizes and sample sizes needed for classifier stability and generalization capability. As an example, the responses of human bone marrow stromal cells (hBMSCs) to fibrous vs flat microenvironments were compared on day 1. Our analysis showed that 57 cells (grouped into supercells of size 4) are the minimum needed for phenotyping. The analysis identified that a combination of minor axis length, solidity, and mean negative curvature were the strongest early shape-based indicator of hBMSCs response to fibrous microenvironment.

Fibers containing 5-amino-2-(p-aminophenyl)benzimidazole are being considered for use as reinforcement in soft body armor applications. Past research in this laboratory has resulted in a suite of tests that have been used to detect degradation in other fibers and are now being applied to the fibers in question. Due to the architecture of the yarns in this study, two methods to extract single filaments for tensile testing were described and analyzed. A dry method resulted in fibers with surface damage, reflected in a high standard deviation in strength. A wet extraction method showed a reduction in surface damage and a lower standard deviation in strength. Fourier Transform Infrared analysis detected signs of hydrolysis in the fibers that were exposed to water. Although no noticeable loss in tensile strength was noted upon exposure, the possibility of hydrolysis in these fibers may indicate a need for further study.

This work presents the implementation in R of the alpha-shape of a finite set of points in the three-dimensional space R-3. This geometric structure generalizes the convex hull and allows to recover the shape of non-convex and even non-connected sets in 3D, given a random sample of points taken into it. Besides the computation of the alpha-shape, the R package alphashape3d provides users with tools to facilitate the three-dimensional graphical visualization of the estimated set as well as the computation of important characteristics such as the connected components or the volume, among others.