Distinct cis-acting regions control six6 expression during eye field and optic cup stages of eye formation.

The eye field transcription factor, Six6, is essential for both the early (specification and proliferative growth) phase of eye formation, as well as for normal retinal progenitor cell differentiation. While genomic regions driving six6 optic cup expression have been described, the sequences controlling eye field and optic vesicle expression are unknown. Two evolutionary conserved regions 5' and a third 3' to the six6 coding region were identified, and together they faithfully replicate the endogenous X. laevis six6 expression pattern. Transgenic lines were generated and used to determine the onset and expression patterns controlled by the regulatory regions. The conserved 3' region was necessary and sufficient for eye field and optic vesicle expression. In contrast, the two conserved enhancer regions located 5' of the coding sequence were required together for normal optic cup and mature retinal expression. Gain-of-function experiments indicate endogenous six6 and GFP expression in F1 transgenic embryos are similarly regulated in response to candidate trans-acting factors. Importantly, CRISPR/CAS9-mediated deletion of the 3' eye field/optic vesicle enhancer in X. laevis, resulted in a reduction in optic vesicle size. These results identify the cis-acting regions, demonstrate the modular nature of the elements controlling early versus late retinal expression, and identify potential regulators of six6 expression during the early stages of eye formation.

Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites.

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realistic quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.

Stability of Ensemble Models Predicts Productivity of Enzymatic Systems.

Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantly in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. The EMRA method incorporates properties of network structure, including stoichiometry and kinetic form, but does not require specific parameter values of the enzymes.

Building carbon-carbon bonds using a biocatalytic methanol condensation cycle.

Methanol is an important intermediate in the utilization of natural gas for synthesizing other feedstock chemicals. Typically, chemical approaches for building C-C bonds from methanol require high temperature and pressure. Biological conversion of methanol to longer carbon chain compounds is feasible; however, the natural biological pathways for methanol utilization involve carbon dioxide loss or ATP expenditure. Here we demonstrated a biocatalytic pathway, termed the methanol condensation cycle (MCC), by combining the nonoxidative glycolysis with the ribulose monophosphate pathway to convert methanol to higher-chain alcohols or other acetyl-CoA derivatives using enzymatic reactions in a carbon-conserved and ATP-independent system. We investigated the robustness of MCC and identified operational regions. We confirmed that the pathway forms a catalytic cycle through (13)C-carbon labeling. With a cell-free system, we demonstrated the conversion of methanol to ethanol or n-butanol. The high carbon efficiency and low operating temperature are attractive for transforming natural gas-derived methanol to longer-chain liquid fuels and other chemical derivatives.

Homologous recombination deficiency and molecular subtype are associated with immunogenicity in ovarian cancer.

Aim: There is an unmet need for predictive biomarkers for immune checkpoint blockade in ovarian cancer. Homologous recombination deficiency (HRD) and immunoreactive molecular subtype may be associated with determinants of immunogenicity. Materials & methods: Neoantigen load, tumor inflammation signature (TIS), immune cell infiltrates and individual immune checkpoints were assessed based on HRD status and molecular subtype. Results: Tumors with HRD demonstrated significantly higher expression of neoantigens and multiple immune check points, but not higher TIS scores or increased immune cell infiltrates. Immunoreactive tumors had significantly higher neoantigen expression, TIS scores, immune cell infiltrate and immune checkpoint expression compared with other subtypes. Conclusion: HRD and the immunoreactive molecular subtype signature were associated with multiple determinants of immunogenicity and deserve further exploration as predictive biomarkers.

A lipid-encapsulated mRNA encoding a potently neutralizing human monoclonal antibody protects against chikungunya infection.

Infection with chikungunya virus (CHIKV) causes an acute illness characterized by fever, rash, and arthralgia. However, CHIKV infection can sometimes progress to chronic arthritis or even lethal disease. CHIKV continues to cause substantial morbidity worldwide as its vector mosquitoes expand and spread. There are currently no approved vaccines or antiviral drugs available for the prevention or treatment of CHIKV. Although antibody therapy has shown promise in the prevention or treatment of CHIKV disease in preclinical models, challenges remain for implementing such therapies. Here, from the B cells of a survivor of natural CHIKV infection, we isolated ultrapotent neutralizing human monoclonal antibodies (mAbs) and encoded their sequences into mRNA molecules delivered by infusion. One human mAb, CHKV-24, was expressed to biologically significant levels in vivo after infusion of mRNAs in lipid nanoparticles in mice. We evaluated the protective capacity of CHKV-24 mAb immunoglobulin G protein or mRNA in mouse models of CHIKV infection. Treatment with CHKV-24 mRNA protected mice from arthritis, musculoskeletal tissue infection, and lethality and reduced viremia to undetectable levels at 2 days after inoculation. Infusion of macaques with CHKV-24 mRNA achieved a mean maximal mAb concentration of 10.1 to 35.9 micrograms per milliliter, with a half-life of 23 days, a level well above what is needed for protection in mice. Studies with CHKV-24 mRNA in macaques demonstrated a dose-response effect after the first dose of mRNA and maintained levels after second dose. These preclinical data with CHKV-24 mRNA suggest that it might be useful to prevent human disease.

Low Concordance of Patient-Reported Outcomes With Clinical and Clinical Trial Documentation.

PURPOSE: Health care research increasingly relies on assessment of data extracted from electronic medical records (EMRs). Clinical trial adverse event (AE) logs and patient-reported outcomes (PROs) are sources of data often available in the context of specific research projects. The aim of this study was to evaluate the extent of data concordance from these sources. PATIENTS AND METHODS: Patients enrolled in clinical trials or receiving standard treatment for lung cancer (n = 62) completed validated questionnaires on physical and psychological symptoms at up to three assessment points. Temporally matched documentation was extracted from EMR notes and, for clinical trial participants (n = 41), AE logs. Evaluated data included symptom assessment, vital signs, medication logs, and laboratory values. Agreement (positive, negative) and Cohen's κ coefficients were calculated to assess concordance of symptoms among sources, with PROs considered the gold standard. RESULTS: Patient-reported weight loss correlated significantly with clinical measurements ( t = 2.90; P = .02), and average number of PROs correlated negatively with albumin concentration, supporting PROs as the gold standard. Comparisons of PROs versus EMR yielded poor concordance across 11 physical symptoms, anxiety, and depressive symptoms (all κ < 0.40). Providers under-reported the presence of each symptom in the EMR compared with PROs. AE logs showed similarly poor concordance with PROs (all κ < 0.40, except shortness of breath). Negative agreement among sources was higher than positive agreement for all symptoms except pain. CONCLUSION: There was poor concordance between EMR notes and AE logs with PROs. Findings suggest that EMR notes and AE logs may not be reliable sources for capturing physical and psychological symptoms experienced by patients with lung cancer, supporting use of PRO assessments in oncology practices.

Metabolic systems modeling for cell factories improvement.

Techniques for modeling microbial bioproduction systems have evolved over many decades. Here, we survey recent literature and focus on modeling approaches for improving bioproduction. These techniques from systems biology are based on different methodologies, starting from stoichiometry only to various stoichiometry with kinetics approaches that address different issues in metabolic systems. Techniques to overcome unknown kinetic parameters using random sampling have emerged to address meaningful questions. Among those questions, pathway robustness seems to be an important issue for metabolic engineering. We also discuss the increasing significance of databases in biology and their potential impact for biotechnology.

A Sensitive IHC Method for Monitoring Autophagy-Specific Markers in Human Tumor Xenografts.

Objective. Use of tyramide signal amplification (TSA) to detect autophagy biomarkers in formalin fixed and paraffin embedded (FFPE) xenograft tissue. Materials and Methods. Autophagy marker regulation was studied in xenograft tissues using Amp HQ IHC and standard IHC methods. Results. The data demonstrate the feasibility of using high sensitivity TSA IHC assays to measure low abundant autophagy markers in FFPE xenograft tissue.

ZFHX4 interacts with the NuRD core member CHD4 and regulates the glioblastoma tumor-initiating cell state.

Glioblastoma (GBM) harbors subpopulations of therapy-resistant tumor-initiating cells (TICs) that are self-renewing and multipotent. To understand the regulation of the TIC state, we performed an image-based screen for genes regulating GBM TIC maintenance and identified ZFHX4, a 397 kDa transcription factor. ZFHX4 is required to maintain TIC-associated and normal human neural precursor cell phenotypes in vitro, suggesting that ZFHX4 regulates differentiation, and its suppression increases glioma-free survival in intracranial xenografts. ZFHX4 interacts with CHD4, a core member of the nucleosome remodeling and deacetylase (NuRD) complex. ZFHX4 and CHD4 bind to overlapping sets of genomic loci and control similar gene expression programs. Using expression data derived from GBM patients, we found that ZFHX4 significantly affects CHD4-mediated gene expression perturbations, which defines ZFHX4 as a master regulator of CHD4. These observations define ZFHX4 as a regulatory factor that links the chromatin-remodeling NuRD complex and the GBM TIC state.

Coordinate activation of Shh and PI3K signaling in PTEN-deficient glioblastoma: new therapeutic opportunities.

In glioblastoma, phosphatidylinositol 3-kinase (PI3K) signaling is frequently activated by loss of the tumor suppressor phosphatase and tensin homolog (PTEN). However, it is not known whether inhibiting PI3K represents a selective and effective approach for treatment. We interrogated large databases and found that sonic hedgehog (SHH) signaling is activated in PTEN-deficient glioblastoma. We demonstrate that the SHH and PI3K pathways synergize to promote tumor growth and viability in human PTEN-deficient glioblastomas. A combination of PI3K and SHH signaling inhibitors not only suppressed the activation of both pathways but also abrogated S6 kinase (S6K) signaling. Accordingly, targeting both pathways simultaneously resulted in mitotic catastrophe and tumor apoptosis and markedly reduced the growth of PTEN-deficient glioblastomas in vitro and in vivo. The drugs tested here appear to be safe in humans; therefore, this combination may provide a new targeted treatment for glioblastoma.

The central nervous system-restricted transcription factor Olig2 opposes p53 responses to genotoxic damage in neural progenitors and malignant glioma.

High-grade gliomas are notoriously insensitive to radiation and genotoxic drugs. Paradoxically, the p53 gene is structurally intact in the majority of these tumors. Resistance to genotoxic modalities in p53-positive gliomas is generally attributed to attenuation of p53 functions by mutations of other components within the p53 signaling axis, such as p14(Arf), MDM2, and ATM, but this explanation is not entirely satisfactory. We show here that the central nervous system (CNS)-restricted transcription factor Olig2 affects a key posttranslational modification of p53 in both normal and malignant neural progenitors and thereby antagonizes the interaction of p53 with promoter elements of multiple target genes. In the absence of Olig2 function, even attenuated levels of p53 are adequate for biological responses to genotoxic damage.