Statistical optimization of cell-hydrogel interactions for green microbiology - a tutorial review.

In this tutorial mini-review, we explore the application of Design of Experiments (DOE) as a powerful statistical tool in biotechnology. Specifically, we review the optimization of hydrogel materials for diverse microbial applications related to green microbiology, the use of microbes to promote sustainability. Hydrogels, three-dimensional polymers networks with high water retention capabilities, are pivotal in the immobilization of microorganisms and provide a customizable environment essential for directing microbial fate. We focus on the application of DOE to precisely tailor hydrogel compositions for a range of fungi and bacteria either used for the sustainable production of chemical compounds, or the elimination of hazardous substances. We examine a variety of DOE design strategies such as central composite designs, Box-Behnken designs, and optimal designs, and discuss their strategic implementation across diverse hydrogel formulations. Our analysis explores the integral role of DOE in refining hydrogels derived from a spectrum of polymers, including natural and synthetic polymers. We illustrate how DOE facilitates nuanced control over hydrogel properties that cannot be achieved using a standard one factor at a time approach. Furthermore, this review reveals a conserved finding across different materials and applications: there are significant interactions between hydrogel parameters and cell behavior. This highlights the intricacies of cell-hydrogel interactions and the impact on hydrogel material properties and cellular functions. Lastly, this review not only highlights DOE's efficacy in streamlining the optimization of cell-hydrogel processes but also positions it as a critical tool in advancing our understanding of cell-hydrogel dynamics, potentially leading to innovative advancements in biotechnological applications and bioengineering solutions.

The optimization of poly(vinyl)-alcohol-alginate beads with a slow-release compound for the aerobic cometabolism of chlorinated aliphatic hydrocarbons.

Chlorinated aliphatic hydrocarbons (CAHs), such as cis-1,2-dichloroethylene (cDCE), are prevalent in groundwater at many locations throughout the United States. When immobilized in hydrogel beads with slow-release compounds, the bacteria strain Rhodococcus rhodochrous ATCC 21198 can be used for the in situ bioremediation of cDCE. These hydrogel beads must exhibit high mechanical strength and resist degradation to extend the lifetime of slow-release compounds and bioremediation. We engineered poly(vinyl)-alcohol - alginate (PVA-AG) beads to immobilize ATCC 21198 with the slow-release compound, tetrabutoxysilane (TBOS) that produces 1-butanol as a growth substrate, for high mechanical strength. We optimized three inputs (concentration of PVA, concentration of AG, and the crosslinking time) on two responses (compressive modulus and rate of oxygen utilization) for batch incubation experiments between 1 and 30 days using a design of experiments approach. The predictive models generated from design of experiments were then tested by measuring the compressive strength, oxygen utilization, and abiotic rates of hydrolysis for a predicted optimal bead formulation. The result of this study generated a hydrogel bead with immobilized R. rhodochrous ATCC 21198 and TBOS that exhibited a high compressive modulus on day 1 and day 30, which was accurately predicted by models. These hydrogel beads exhibited low metabolic activity based on oxygen rates on day 1 and day 30 but were not accurately predicted by the models. In addition, the ratio between oxygen utilization and abiotic rates of hydrolysis were observed to be roughly half of what was expected stoichiometrically. Lastly, we demonstrated the capability to use these beads as a bioremediation technology for cDCE as we found that, for all bead formulations, cDCE was significantly reduced after 30 days. Altogether, this work demonstrates the capability to capture and enhance the material properties of the complex hydrogel beads with predictive models yet signals the need for more robust methods to understand the metabolic activity that occurs in the hydrogel beads.

Statistical optimization of hydrazone-crosslinked hyaluronic acid hydrogels for protein delivery.

Hydrazone-crosslinked hydrogels are attractive protein delivery vehicles for regenerative medicine. However, each regenerative medicine application requires unique hydrogel properties to achieve an ideal outcome. The properties of a hydrogel can be impacted by numerous factors involved in its fabrication. We used design of experiments (DoE) statistical modeling to efficiently optimize the physicochemical properties of a hyaluronic acid (HA) hydrazone-crosslinked hydrogel for protein delivery for bone regeneration. We modified HA with either adipic acid dihydrazide (HA-ADH) or aldehyde (HA-Ox) functional groups and used DoE to evaluate the interactions of three input variables, the molecular weight of HA (40 or 100 kDa), the concentration of HA-ADH (1-3% w/v), and the concentration of HA-Ox (1-3% w/v), on three output responses, gelation time, compressive modulus, and hydrogel stability over time. We identified 100 kDa HA-ADH3.00HA-Ox2.33 as an optimal hydrogel that met all of our design criteria, including displaying a gelation time of 3.7 minutes, compressive modulus of 62.1 Pa, and minimal mass change over 28 days. For protein delivery, we conjugated affinity proteins called affibodies that were specific to the osteogenic protein bone morphogenetic protein-2 (BMP-2) to HA hydrogels and demonstrated that our platform could control the release of BMP-2 over 28 days. Ultimately, our approach demonstrates the utility of DoE for optimizing hydrazone-crosslinked HA hydrogels for protein delivery.

Characterizing the Extracellular Matrix Transcriptome of Endometriosis.

In recent years, the matrisome, a set of proteins that make up the extracellular matrix (ECM) or are closely involved in ECM behavior, has been shown to have great importance for characterizing and understanding disease pathogenesis and progression. The matrisome is especially critical for examining diseases characterized by extensive tissue remodeling. Endometriosis is characterized by the extrauterine growth of endometrial tissue, making it an ideal condition to study through the lens of matrisome gene expression. While large gene expression datasets have become more available and gene dysregulation in endometriosis has been the target of several studies, the gene expression profile of the matrisome specifically in endometriosis has not been well characterized. In our study, we explored four Gene Expression Omnibus (GEO) DNA microarray datasets containing eutopic endometrium of people with and without endometriosis. After batch correction, menstrual cycle phase accounted for 53% of variance and disease accounted for 23%; thus, the data were separated by menstrual cycle phase before performing differential expression analysis, statistical and machine learning modeling, and enrichment analysis. We established that matrisome gene expression alone can effectively differentiate endometriosis samples from healthy ones, demonstrating the potential of matrisome gene expression for diagnostic applications. Furthermore, we identified specific matrisome genes and gene networks whose expression can distinguish endometriosis stages I/II from III/IV. Taken together, these findings may aid in developing future in vitro models of disease, offer insights into novel treatment strategies, and advance diagnostic tools for this underserved patient population.

Statistical Optimization of Hydrazone-Crosslinked Hyaluronic Acid Hydrogels for Protein Delivery.

Hydrazone-crosslinked hydrogels are attractive protein delivery vehicles for regenerative medicine. However, each regenerative medicine application requires unique hydrogel properties to achieve an ideal outcome. The properties of a hydrogel can be impacted by numerous factors involved in its fabrication. We used design of experiments (DoE) statistical modeling to efficiently optimize the physicochemical properties of a hyaluronic acid (HA) hydrazone-crosslinked hydrogel for protein delivery for bone regeneration. We modified HA with either adipic acid dihydrazide (HA-ADH) or aldehyde (HA-Ox) functional groups and used DoE to evaluate the interactions of three input variables, the molecular weight of HA (40 or 100 kDa), the concentration of HA-ADH (1-3% w/v), and the concentration of HA-Ox (1-3% w/v), on three output responses, gelation time, compressive modulus, and hydrogel stability over time. We identified 100 kDa HA-ADH3.0HA-Ox2.33 as an optimal hydrogel that met all of our design criteria, including displaying a gelation time of 3.7 minutes, compressive modulus of 62.1 Pa, and minimal mass change over 28 days. For protein delivery, we conjugated affinity proteins called affibodies that were specific to the osteogenic protein bone morphogenetic protein-2 (BMP-2) to HA hydrogels and demonstrated that our platform could control the release of BMP-2 over 28 days. Ultimately, our approach demonstrates the utility of DoE for optimizing hydrazone-crosslinked HA hydrogels for protein delivery.

Engineering high throughput screening platforms of cervical cancer.

Cervical cancer is the second leading cause of cancer-related death in women under 40 and is one of the few cancers to have an increased incidence rate and decreased survival rate over the last 10 years. One in five patients will have recurrent and/or distant metastatic disease and these patients face a 5-year survival rate of less than 17%. Thus, there is a pressing need to develop new anticancer therapeutics for this underserved patient population. However, the development of new anticancer drugs remains a challenge, as only 7% of novel anticancer drugs are approved for clinical use. To facilitate identification of novel and effective anticancer drugs for cervical cancer, we developed a multilayer multicellular platform of human cervical cancer cell lines and primary human microvascular endothelial cells that interfaces with high throughput drug screening methods to evaluate the anti-metastatic and anti-angiogenic drug efficacy simultaneously. Through the use of design of experiments statistical optimization, we identified the specific concentrations of collagen I, fibrinogen, fibronectin, GelMA, and PEGDA in each hydrogel layer that maximized both cervical cancer invasion and endothelial microvessel length. We then validated the optimized platform and assessed its viscoelastic properties. Finally, using this optimized platform, we conducted a targeted drug screen of four clinically relevant drugs on two cervical cancer cell lines. Overall, this work provides a valuable platform that can be used to screen large compound libraries for mechanistic studies, drug discovery, and precision oncology for cervical cancer patients.

Characterizing the extracellular matrix transcriptome of cervical, endometrial, and uterine cancers.

Increasingly, the matrisome, a set of proteins that form the core of the extracellular matrix (ECM) or are closely associated with it, has been demonstrated to play a key role in tumor progression. However, in the context of gynecological cancers, the matrisome has not been well characterized. A holistic, yet targeted, exploration of the tumor microenvironment is critical for better understanding the progression of gynecological cancers, identifying key biomarkers for cancer progression, establishing the role of gene expression in patient survival, and for assisting in the development of new targeted therapies. In this work, we explored the matrisome gene expression profiles of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), uterine corpus endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS) using publicly available RNA-seq data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) portal. We hypothesized that the matrisomal expression patterns of CESC, UCEC, and UCS would be highly distinct with respect to genes which are differentially expressed and hold inferential significance with respect to tumor progression, patient survival, or both. Through a combination of statistical and machine learning analysis techniques, we identified sets of genes and gene networks which characterized each of the gynecological cancer cohorts. Our findings demonstrate that the matrisome is critical for characterizing gynecological cancers and transcriptomic mechanisms of cancer progression and outcome. Furthermore, while the goal of pan-cancer transcriptional analyses is often to highlight the shared attributes of these cancer types, we demonstrate that they are highly distinct diseases which require separate analysis, modeling, and treatment approaches. In future studies, matrisome genes and gene ontology terms that were identified as holding inferential significance for cancer stage and patient survival can be evaluated as potential drug targets and incorporated into in vitro models of disease.

Quantitative Analysis of the Extracellular Matrix by Immunoblot.

Knowing the global and local concentration of extracellular matrix proteins provides critical information for building tissue engineered constructs of healthy and diseased tissue. Here we describe a method of integrating quantitative dot blot along with immunohistochemistry on the same patient sample in order to calculate the overall protein concentration as well as the concentration in a region of interest.

Biomaterial strategies to replicate gynecological tissue.

Women's health is an important and understudied area of research. The current standard of care for many gynecological diseases such as cancer or autoimmune-linked disorders such as endometriosis is surgery; however, the underlying mechanisms of action of many gynecological diseases are poorly understood. The field of tissue engineering has the potential to transform the field of women's health by developing in vitro models of healthy and diseased tissue that could be used to identify novel treatment strategies as well as gain a better understanding of complex signaling dynamics. Identification of the appropriate biomaterials, cell types, and stimuli (the tissue engineering triad) needed to build these in vitro models can be gleaned by interrogating the underlying extracellular matrix, cell organization, and soluble factors present in the tissue. In this review, we provide a general overview of the biology and components of the major tissues that make up the female reproductive system (ovaries, fallopian tubes, the uterus, and cervix) as well as a comprehensive survey of the different biomaterials that have been chosen to build in vitro models of these tissues. Furthermore, for each tissue, we recommend guiding principles in the design of in vitro models and discuss their potential to be used in drug screening and mechanistic studies.

Ovarian cancer cells direct monocyte differentiation through a non-canonical pathway.

BACKGROUND: Alternatively-activated macrophages (AAMs), an anti-inflammatory macrophage subpopulation, have been implicated in the progression of high grade serous ovarian carcinoma (HGSOC). Increased levels of AAMs are correlated with poor HGSOC survival rates, and AAMs increase the attachment and spread of HGSOC cells in vitro. However, the mechanism by which monocytes in the HGSOC tumor microenvironment are differentiated and polarized to AAMs remains unknown. METHODS: Using an in vitro co-culture device, we cultured naïve, primary human monocytes with a panel of five HGSOC cell lines over the course of 7 days. An empirical Bayesian statistical method, EBSeq, was used to couple RNA-seq with observed monocyte-derived cell phenotype to explore which HGSOC-derived soluble factors supported differentiation to CD68+ macrophages and subsequent polarization towards CD163+ AAMs. Pathways of interest were interrogated using small molecule inhibitors, neutralizing antibodies, and CRISPR knockout cell lines. RESULTS: HGSOC cell lines displayed a wide range of abilities to generate AAMs from naïve monocytes. Much of this variation appeared to result from differential ability to generate CD68+ macrophages, as most CD68+ cells were also CD163+. Differences in tumor cell potential to generate macrophages was not due to a MCSF-dependent mechanism, nor variance in established pro-AAM factors. TGFα was implicated as a potential signaling molecule produced by tumor cells that could induce macrophage differentiation, which was validated using a CRISPR knockout of TGFA in the OVCAR5 cell line. CONCLUSIONS: HGSOC production of TGFα drives monocytes to differentiate into macrophages, representing a central arm of the mechanism by which AAMs are generated in the tumor microenvironment.

Ovarian Cells Have Increased Proliferation in Response to Heparin-Binding Epidermal Growth Factor as Collagen Density Increases.

It is well known that during ovarian cancer progression, the omentum transforms from a thin lacy organ to a thick tougher tissue. However, the mechanisms regulating this transformation and the implications of the altered microenvironment on ovarian cancer progression remain unclear. To address these questions, the global and local concentrations of collagen I were determined for normal and metastatic human omentum. Collagen I was increased 5.3-fold in omenta from ovarian cancer patients and localized to areas of activated fibroblasts rather than regions with a high density of cancer cells. Transforming growth factor beta 1 (TGFß1) was detected in ascites from ovarian cancer patients (4 ng/mL), suggesting a potential role for TGFß1 in the observed increase in collagen. Treatment with TGFß1 induced fibroblast activation, proliferation, and collagen deposition in mouse omental explants and an in vitro model with human omental fibroblasts. Finally, the impact of increased collagen I on ovarian cancer cells was determined by examining proliferation on collagen I gels formulated to mimic normal and cancerous omenta. While collagen density alone had no impact on proliferation, a synergistic effect was observed with collagen density and heparin-binding epidermal growth factor treatment. These results suggest that TGFß1 induces collagen deposition from the resident fibroblasts in the omentum and that this altered microenvironment impacts cancer cell response to growth factors found in ascites. Impact statement Using quantitative analysis of patient samples, in vitro models of the metastatic ovarian cancer microenvironment were designed with pathologically relevant collagen densities and growth factor concentrations. Studies in these models support a mechanism where transforming growth factor ß1 in the ascites fluid induces omental fibroblast proliferation, activation, and deposition of collagen I, which then impacts tumor cell proliferation in response to additional ascites growth factors such as heparin-binding epidermal growth factor. This approach can be used to dissect mechanisms involved in microenvironmental modeling in multiple disease applications.

Alternatively activated macrophage-derived secretome stimulates ovarian cancer spheroid spreading through a JAK2/STAT3 pathway.

High-grade serous ovarian cancer (HGSOC) metastasizes when tumor spheroids detach from the primary tumor and re-attach throughout the peritoneal cavity. Once the cancer cells have implanted in these new sites, the development of metastatic lesions is dependent on the disaggregation of cancer cells from the spheroids and subsequent expansion across the collagenous extracellular matrix (ECM). As HGSOC progresses an increase in alternatively activated macrophages (AAMs) in the surrounding ascites fluid has been observed and AAMs have been shown to enhance tumor invasion and growth in a wide range of cancers. We hypothesized that soluble factors from AAMs in the peritoneal microenvironment promote the disaggregation of ovarian cancer spheroids across the underlying ECM. We determined that co-culture with AAMs significantly increased HGSOC spheroid spreading across a collagen matrix. Multivariate modeling identified AAM-derived factors that correlated with enhanced spread of HGSOC spheroids and experimental validation showed that each individual cell line responded to a distinct AAM-derived factor (FLT3L, leptin, or HB-EGF). Despite this ligand-level heterogeneity, we determined that the AAM-derived factors utilized a common signaling pathway to induce spheroid spreading: JAK2/STAT3 activation followed by MMP-9 mediated spreading. Furthermore, immunostaining demonstrated that FLT3, LEPR, EGFR, and pSTAT3 were upregulated in metastases in HGSOC patients, with substantial patient-to-patient heterogeneity. These results suggest that inhibiting individual soluble factors will not inhibit AAM-induced effects across a broad group of patients; instead, the downstream JAK2/STAT3/MMP-9 pathway should be examined as potential therapeutic targets to slow metastasis in ovarian cancer.

Alternatively-Activated Macrophages Upregulate Mesothelial Expression of P-Selectin to Enhance Adhesion of Ovarian Cancer Cells.

Peritoneal metastasis of high-grade serous ovarian cancer (HGSOC) occurs when tumor cells suspended in ascites adhere to mesothelial cells. Despite the strong relationship between metastatic burden and prognosis in HGSOC, there are currently no therapies specifically targeting the metastatic process. We utilized a coculture model and multivariate analysis to examine how interactions between tumor cells, mesothelial cells, and alternatively-activated macrophages (AAM) influence the adhesion of tumor cells to mesothelial cells. We found that AAM-secreted MIP-1ß activates CCR5/PI3K signaling in mesothelial cells, resulting in expression of P-selectin on the mesothelial cell surface. Tumor cells attached to this de novo P-selectin through CD24, resulting in increased tumor cell adhesion in static conditions and rolling underflow. C57/BL6 mice treated with MIP-1ß exhibited increased P-selectin expression on mesothelial cells lining peritoneal tissues, which enhanced CaOV3 adhesion ex vivo and ID8 adhesion in vivo Analysis of samples from patients with HGSOC confirmed increased MIP-1ß and P-selectin, suggesting that this novel multicellular mechanism could be targeted to slow or stop metastasis in HGSOC by repurposing anti-CCR5 and P-selectin therapies developed for other indications.Significance: This study reports novel insights on the peritoneal dissemination occurring during progression of ovarian cancer and has potential for therapeutic intervention.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/13/3560/F1.large.jpg Cancer Res; 78(13); 3560-73. ©2018 AACR.