Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases.

Purpose: To assess the impact of ocular confounding factors on aqueous humor (AH) proteomic and metabolomic analyses for retinal disease characterization. Methods: This study recruited 138 subjects (eyes): 102 with neovascular age-related macular degeneration (nAMD), 18 with diabetic macular edema (DME), and 18 with cataract (control group). AH samples underwent analysis using Olink Target 96 proteomics and Metabolon's metabolomics platform Data analysis included correlation, differential abundance, and gene-set analysis. Results: In total, 756 proteins and 408 metabolites were quantified in AH. Total AH protein concentration was notably higher in nAMD (3.2-fold) and DME (4.1-fold) compared to controls. Pseudophakic eyes showed higher total AH protein concentrations than phakic eyes (e.g., 1.6-fold in nAMD) and a specific protein signature indicative of matrix remodeling. Unexpectedly, pupil-dilating drugs containing phenylephrine/tropicamide increased several AH proteins, notably interleukin-6 (5.4-fold in nAMD). Correcting for these factors revealed functionally relevant protein correlation clusters and disease-relevant, differentially abundant proteins across the groups. Metabolomics analysis, for which the relevance of confounder adjustment was less apparent, suggested insufficiently controlled diabetes and chronic hyperglycemia in the DME group. Conclusions: AH protein concentration, pseudophakia, and pupil dilation with phenylephrine/tropicamide are important confounding factors for AH protein analyses. When these factors are considered, AH analyses can more clearly reveal disease-relevant factors. Translational Relevance: Considering AH protein concentration, lens status, and phenylephrine/tropicamide administration as confounders is crucial for accurate interpretation of AH protein data.

Correlation of Aqueous, Vitreous, and Serum Protein Levels in Patients With Retinal Diseases.

Purpose: To further establish aqueous humor (AH) as a clinically suitable source of protein biomarkers in retinal diseases by evaluating the correlation of a large panel of proteins between AH, vitreous humor (VH), and serum (SE). Methods: We enrolled 60 subjects (eyes) with various non-infectious retinal diseases. AH, VH, and SE proteins were analyzed using the Olink Target 96 platform (1196 protein assays in total). We compared these three matrices in terms of quantification overlap, principal component analysis, and correlation. Results: In the AH, VH, and SE samples, 841, 917, and 1133 proteins, respectively, were consistently quantified above the limit of detection in more than 30% of patients. AH and VH shared 812 of these proteins. AH and VH samples overlapped along principal component 1, but SE samples were distinct. We identified 490 proteins with significant (false discovery rate [FDR]-adjusted P < 0.05) and relevant correlations (correlation coefficient > 0.5) between AH and VH, compared to only 33 and 40 proteins for VH and SE and for AH and SE, respectively. Conclusions: Due to a close correlation between protein concentrations in the AH and VH and a clear difference from the SE, AH has the potential to serve as a substitute for VH and may hold significance in identifying protein biomarkers and novel targets related to retinal diseases. Translational Relevance: This study further supports AH as a clinically suitable source of protein biomarkers in retinal diseases. In addition, the identified AH and VH correlations can inform the selection of protein biomarker candidates in future translational research.

Prospective multicentre study of host response signatures in neonatal sepsis in Sub Saharan Africa.

Few biomarkers for sepsis diagnosis are commonly used in neonatal sepsis. While the role of host response is increasingly recognized in sepsis pathogenesis and prognosis, there is a need for evaluating new biomarkers targeting host response in regions where sepsis burden is high and medico-economic resources are scarce. The objective of the study is to evaluate diagnostic and prognostic accuracy of biomarkers of neonatal sepsis in Sub Saharan Africa. This prospective multicentre study included newborn infants delivered in the Abomey-Calavi region in South Benin and their follow-up from birth to 3 months of age. Accuracy of transcriptional (CD74, CX3CR1), proteic (PCT, IL-6, IL-10, IP-10) biomarkers and clinical characteristics to diagnose and prognose neonatal sepsis were measured. At delivery, cord blood from all consecutive newborns were sampled and analysed, and infants were followed for a 12 weeks' period. Five hundred and eighty-one newborns were enrolled. One hundred and seventy-two newborns developed neonatal sepsis (29.6%) and death occurred in forty-nine infants (8.4%). Although PCT, IL-6 and IP-10 levels were independently associated with sepsis diagnosis, diagnostic accuracy of clinical variables combinations was similar to combinations with biomarkers and superior to biomarkers alone. Nonetheless, CD74, being the only biomarkers independently associated with mortality, showed elevated prognosis accuracy (AUC > 0.9) either alone or in combination with other biomarkers (eg. CD74/IP-10) or clinical criterion (eg. Apgar 1, birth weight). These results suggest that cord blood PCT had a low accuracy for diagnosing early onset neonatal sepsis in Sub Saharan African neonates, while association of clinical criterion showed to be more accurate than any biomarkers taken independently. At birth, CD74, either associated with IP-10 or clinical criterion, had the best accuracy in prognosing sepsis mortality.Trial registration Clinicaltrial.gov registration number: NCT03780712. Registered 19 December 2018. Retrospectively registered.

Differential response induced by LPS and MPLA in immunocompetent and septic individuals.

Lipopolysaccharide (LPS) and monophosphoryl lipid A (MPLA) induce, overall, similar transcriptional profiles in healthy individuals, although LPS has been shown to more potently induce pro-inflammatory cytokines. We explore herein whether MPLA could be considered as a synthetic replacement of LPS in immune functional assays to study anergy of immune cells in septic patients. Ex vivo whole blood stimulation with MPLA revealed a lower induction of the TNFα secreted protein in 20 septic patients (SP) compared to 10 healthy volunteers (HV), in agreement with monocyte anergy. Principal component analysis of the 93-gene molecular response to MPLA and LPS stimulation found that the main variability was driven by stimulation in HV and by pathophysiology in SP. MPLA was a stronger inducer of the HLA family genes than LPS in both populations, arguing for divergent signalling pathways downstream of TLR-4. In addition, MPLA appeared to present a more informative stratification potential within the septic population.

Deciphering heterogeneity of septic shock patients using immune functional assays: a proof of concept study.

The complexity of sepsis pathophysiology hinders patient management and therapeutic decisions. In this proof-of-concept study we characterised the underlying host immune response alterations using a standardised immune functional assay (IFA) in order to stratify a sepsis population. In septic shock patients, ex vivo LPS and SEB stimulations modulated, respectively, 5.3% (1/19) and 57.1% (12/21) of the pathways modulated in healthy volunteers (HV), highlighting deeper alterations induced by LPS than by SEB. SEB-based clustering, identified 3 severity-based groups of septic patients significantly different regarding mHLA-DR expression and TNFα level post-LPS, as well as 28-day mortality, and nosocomial infections. Combining the results from two independent cohorts gathering 20 HV and 60 patients, 1 cluster grouped all HV with 12% of patients. The second cluster grouped 42% of patients and contained all non-survivors. The third cluster grouped 46% of patients, including 78% of those with nosocomial infections. The molecular features of these clusters indicated a distinctive contribution of previously described genes defining a "healthy-immune response" and a "sepsis-related host response". The third cluster was characterised by potential immune recovery that underlines the possible added value of SEB-based IFA to capture the sepsis immune response and contribute to personalised management.

Towards standardization of immune functional assays.

Recent advances in the immunotherapy field require evaluation of the immune function to adapt therapeutic decisions. Immune functional assays (IFA) are able to reveal the immune status and would be useful to further adapt and/or improve patient's care. However, standardized methods are needed to implement IFA in clinical settings. We carried out an independent validation of a published method used to characterize the underlying host response to infectious conditions using an IFA. We evaluated the reproducibility and robustness of this IFA and the associated readout using an independent healthy volunteers (HV) cohort. Expression of a 44-gene signature and IFNγ protein secretion was assessed after stimulation. We observed a strong host-response correlation between the two cohorts. We also highlight that standardized methods for immune function evaluation exist and could be implemented in larger-scale studies. This IFA could be a relevant tool to reveal innate and adaptive immune dysfunction in immune-related disorders patients.

MixMC: A Multivariate Statistical Framework to Gain Insight into Microbial Communities.

Culture independent techniques, such as shotgun metagenomics and 16S rRNA amplicon sequencing have dramatically changed the way we can examine microbial communities. Recently, changes in microbial community structure and dynamics have been associated with a growing list of human diseases. The identification and comparison of bacteria driving those changes requires the development of sound statistical tools, especially if microbial biomarkers are to be used in a clinical setting. We present mixMC, a novel multivariate data analysis framework for metagenomic biomarker discovery. mixMC accounts for the compositional nature of 16S data and enables detection of subtle differences when high inter-subject variability is present due to microbial sampling performed repeatedly on the same subjects, but in multiple habitats. Through data dimension reduction the multivariate methods provide insightful graphical visualisations to characterise each type of environment in a detailed manner. We applied mixMC to 16S microbiome studies focusing on multiple body sites in healthy individuals, compared our results with existing statistical tools and illustrated added value of using multivariate methodologies to fully characterise and compare microbial communities.

Engineering of a Synthetic Metabolic Pathway for the Assimilation of (d)-Xylose into Value-Added Chemicals.

A synthetic pathway for (d)-xylose assimilation was stoichiometrically evaluated and implemented in Escherichia coli strains. The pathway proceeds via isomerization of (d)-xylose to (d)-xylulose, phosphorylation of (d)-xylulose to obtain (d)-xylulose-1-phosphate (X1P), and aldolytic cleavage of the latter to yield glycolaldehyde and DHAP. Stoichiometric analyses showed that this pathway provides access to ethylene glycol with a theoretical molar yield of 1. Alternatively, both glycolaldehyde and DHAP can be converted to glycolic acid with a theoretical yield that is 20% higher than for the exclusive production of this acid via the glyoxylate shunt. Simultaneous expression of xylulose-1 kinase and X1P aldolase activities, provided by human ketohexokinase-C and human aldolase-B, respectively, restored growth of a (d)-xylulose-5-kinase mutant on xylose. This strain produced ethylene glycol as the major metabolic endproduct. Metabolic engineering provided strains that assimilated the entire C2 fraction into the central metabolism or that produced 4.3 g/L glycolic acid at a molar yield of 0.9 in shake flasks.

Optimization of ethylene glycol production from (D)-xylose via a synthetic pathway implemented in Escherichia coli.

BACKGROUND: Ethylene glycol (EG) is a bulk chemical that is mainly used as an anti-freezing agent and a raw material in the synthesis of plastics. Production of commercial EG currently exclusively relies on chemical synthesis using fossil resources. Biochemical production of ethylene glycol from renewable resources may be more sustainable. RESULTS: Herein, a synthetic pathway is described that produces EG in Escherichia coli through the action of (D)-xylose isomerase, (D)-xylulose-1-kinase, (D)-xylulose-1-phosphate aldolase, and glycolaldehyde reductase. These reactions were successively catalyzed by the endogenous xylose isomerase (XylA), the heterologously expressed human hexokinase (Khk-C) and aldolase (Aldo-B), and an endogenous glycolaldehyde reductase activity, respectively, which we showed to be encoded by yqhD. The production strain was optimized by deleting the genes encoding for (D)-xylulose-5 kinase (xylB) and glycolaldehyde dehydrogenase (aldA), and by overexpressing the candidate glycolaldehyde reductases YqhD, GldA, and FucO. The strain overproducing FucO was the best EG producer reaching a molar yield of 0.94 in shake flasks, and accumulating 20 g/L EG with a molar yield and productivity of 0.91 and 0.37 g/(L.h), respectively, in a controlled bioreactor under aerobic conditions. CONCLUSIONS: We have demonstrated the feasibility to produce EG from (D)-xylose via a synthetic pathway in E. coli at approximately 90 % of the theoretical yield.