Examining the biological pathways underlying clinical heterogeneity in Sjogren's syndrome: proteomic and network analysis.

OBJECTIVES: Stratification approaches are vital to address clinical heterogeneity in Sjogren's syndrome (SS). We previously described that the Newcastle Sjogren's Stratification Tool (NSST) identified four distinct clinical subtypes of SS. We performed proteomic and network analysis to analyse the underlying pathobiology and highlight potential therapeutic targets for different SS subtypes. METHOD: We profiled serum proteins using O-link technology of 180 SS subjects. We used 5 O-link proteomics panels which included a total of 454 unique proteins. Network reconstruction was performed using the ARACNE algorithm, with differential expression estimates overlaid on these networks to reveal the key subnetworks of differential expression. Furthermore, data from a phase III trial of tocilizumab in SS were reanalysed by stratifying patients at baseline using NSST. RESULTS: Our analysis highlights differential expression of chemokines, cytokines and the major autoantigen TRIM21 between the SS subtypes. Furthermore, we observe differential expression of several transcription factors associated with energy metabolism and redox balance namely APE1/Ref-1, FOXO1, TIGAR and BACH1. The differentially expressed proteins were inter-related in our network analysis, supporting the concept that distinct molecular networks underlie the clinical subtypes of SS. Stratification of patients at baseline using NSST revealed improvement of fatigue score only in the subtype expressing the highest levels of serum IL-6. CONCLUSIONS: Our data provide clues to the pathways contributing to the glandular and non-glandular manifestations of SS and to potential therapeutic targets for different SS subtypes. In addition, our analysis highlights the need for further exploration of altered metabolism and mitochondrial dysfunction in the context of SS subtypes.

Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS).

The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain (Norton et al. 2019, https://doi.org/10.5194/bg-16-3069-2019). Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012-2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year-1, about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr-1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.

What can patients tell us in Sjögren's syndrome?

In Sjögren's Syndrome (SS), clinical heterogeneity and discordance between disease activity measures and patient experience are key obstacles to effective therapeutic development. Patient reported outcome measures (PROMs) are useful tools for understanding the unmet needs from the patients' perspective and therefore they are key for the development of patient centric healthcare systems. Initial concern about the subjectivity of PROMs has given way to methodological rigour and clear guidance for the development of PROMs. To date, several studies of patient stratification using PROMs have identified similar symptom-based subgroups. There is evidence to suggest that these subgroups may represent different disease endotypes with differing responses to therapeutic interventions. Stratified medicine approaches, alongside sensitive outcome measures, have the potential to improve our understanding of SS pathobiology and therapeutic development. The inclusion of PROMs is important for the success of such approaches. In this review we discuss the opportunities of using PROMs in understanding the pathogenesis of and therapeutic development for SS.

A role for macrophages under cytokine control in mediating resistance to ADI-PEG20 (pegargiminase) in ASS1-deficient mesothelioma.

BACKGROUND: Pegylated arginine deiminase (ADI-PEG20; pegargiminase) depletes arginine and improves survival outcomes for patients with argininosuccinate synthetase 1 (ASS1)-deficient malignant pleural mesothelioma (MPM). Optimisation of ADI-PEG20-based therapy will require a deeper understanding of resistance mechanisms, including those mediated by the tumor microenvironment. Here, we sought to reverse translate increased tumoral macrophage infiltration in patients with ASS1-deficient MPM relapsing on pegargiminase therapy. METHODS: Macrophage-MPM tumor cell line (2591, MSTO, JU77) co-cultures treated with ADI-PEG20 were analyzed by flow cytometry. Microarray experiments of gene expression profiling were performed in ADI-PEG20-treated MPM tumor cells, and macrophage-relevant genetic "hits" were validated by qPCR, ELISA, and LC/MS. Cytokine and argininosuccinate analyses were performed using plasma from pegargiminase-treated patients with MPM. RESULTS: We identified that ASS1-expressing macrophages promoted viability of ADI-PEG20-treated ASS1-negative MPM cell lines. Microarray gene expression data revealed a dominant CXCR2-dependent chemotactic signature and co-expression of VEGF-A and IL-1α in ADI-PEG20-treated MPM cell lines. We confirmed that ASS1 in macrophages was IL-1α-inducible and that the argininosuccinate concentration doubled in the cell supernatant sufficient to restore MPM cell viability under co-culture conditions with ADI-PEG20. For further validation, we detected elevated plasma VEGF-A and CXCR2-dependent cytokines, and increased argininosuccinate in patients with MPM progressing on ADI-PEG20. Finally, liposomal clodronate depleted ADI-PEG20-driven macrophage infiltration and suppressed growth significantly in the MSTO xenograft murine model. CONCLUSIONS: Collectively, our data indicate that ADI-PEG20-inducible cytokines orchestrate argininosuccinate fuelling of ASS1-deficient mesothelioma by macrophages. This novel stromal-mediated resistance pathway may be leveraged to optimize arginine deprivation therapy for mesothelioma and related arginine-dependent cancers.

Dense canopies browning overshadowed by global greening dominant in sparse canopies.

Greening, an increase in photosynthetically active plant biomass, has been widely reported as period-related and region-specific. We hypothesized that vegetation trends were highly density-dependent with intensified browning in dense canopies and increased greening in sparse canopies. We exploited this insight by estimating vegetation trends in peak growth from dense to sparse canopies graded from 1 to 20 using the non-parametric Mann-Kendall trend test based on the 500 m 8-day composite MODIS Near Infrared Reflectance of terrestrial vegetation (NIRv) time series datasets in the past two decades (2001-2019) at the global scale. We found that global greening increased by 1.42% per grade with strong fit before grade 15 (R2 = 0.95): net browning (11% browning vs 9% greening) exhibited in high-density canopies (NIRv > 0.39) in contrast to 32% greening in low-density canopies (NIRv ≈ 0.15). While the density-dependent greening was evidenced across different biomes and ecosystems, the steepest gradient (changes per grade) in cropland highlighted the increasingly intensified agricultural activities globally. Greening gradients declined in the dryland, but enhanced in the High-latitude ecosystems driven by warming, especially in the shrubland. Density-dependent vegetation trends were accounted for by the disproportionately impacts from climate changes and the unequal contributions of Land Cover Changes (LCC) among dense and sparse canopies. Vegetation trends and greening gradients could be extensively facilitated by Wetting or Decreasing solar Radiation (WDR), especially in sparse grassland and shrubland. Browning was dominant in dense canopies, which was further aggravated by Drying and Increasing solar Radiation (DIR), especially woody vegetation. This study implied the widespread degradation or mortality of highly productive vegetation hidden among global greening dominant in open ecosystems, which might be further exacerbated by the predicted increasing drought under global warming.

Soil exchange rates of COS and CO18O differ with the diversity of microbial communities and their carbonic anhydrase enzymes.

Differentiating the contributions of photosynthesis and respiration to the global carbon cycle is critical for improving predictive climate models. Carbonic anhydrase (CA) activity in leaves is responsible for the largest biosphere-atmosphere trace gas fluxes of carbonyl sulfide (COS) and the oxygen-18 isotopologue of carbon dioxide (CO18O) that both reflect gross photosynthetic rates. However, CA activity also occurs in soils and will be a source of uncertainty in the use of COS and CO18O as carbon cycle tracers until process-based constraints are improved. In this study, we measured COS and CO18O exchange rates and estimated the corresponding CA activity in soils from a range of biomes and land use types. Soil CA activity was not uniform for COS and CO2, and patterns of divergence were related to microbial community composition and CA gene expression patterns. In some cases, the same microbial taxa and CA classes catalyzed both COS and CO2 reactions in soil, but in other cases the specificity towards the two substrates differed markedly. CA activity for COS was related to fungal taxa and ß-D-CA expression, whereas CA activity for CO2 was related to algal and bacterial taxa and α-CA expression. This study integrates gas exchange measurements, enzyme activity models, and characterization of soil taxonomic and genetic diversity to build connections between CA activity and the soil microbiome. Importantly, our results identify kinetic parameters to represent soil CA activity during application of COS and CO18O as carbon cycle tracers.

Automated system for simultaneous analysis of delta(13)C, delta(18)O and CO(2) concentrations in small air samples.

In this paper we present an automated system for simultaneous measurement of CO(2) concentration, delta(13)C and delta(18)O from small (<1 mL) air samples in a short period of time (approximately 1 hour). This system combines continuous-flow isotope ratio mass spectrometry (CF-IRMS) and gas chromatography (GC) with an inlet system similar to conventional dual-inlet methods permitting several measurement cycles of standard and sample air. Analogous to the dual-inlet method, the precision of this system increases with the number of replicate cycles measured. The standard error of the mean for a measurement with this system is 0.7 ppm for the CO(2) concentration and 0.05 per thousand for the delta(13)C and delta(18)O with four replicate cycles and 0.4 ppm and 0.03 per thousand respectively with nine replicate cycles. The mean offset of our measurements from NOAA/CMDL analyzed air samples was 0.08 ppm for the CO(2) concentration, 0.01 per thousand for delta(13)C and 0.00 per thousand for delta(18)O. A specific list of the parts and operation of the system is detailed as well as some of the applications for micrometeorological and ecophysiological applications.