Fecal microbiome variation in the average, healthy population has remained under-investigated. Here, we analyzed two independent, extensively phenotyped cohorts: the Belgian Flemish Gut Flora Project (FGFP; discovery cohort; N = 1106) and the Dutch LifeLines-DEEP study (LLDeep; replication; N = 1135). Integration with global data sets (N combined = 3948) revealed a 14-genera core microbiota, but the 664 identified genera still underexplore total gut diversity. Sixty-nine clinical and questionnaire-based covariates were found associated to microbiota compositional variation with a 92% replication rate. Stool consistency showed the largest effect size, whereas medication explained largest total variance and interacted with other covariate-microbiota associations. Early-life events such as birth mode were not reflected in adult microbiota composition. Finally, we found that proposed disease marker genera associated to host covariates, urging inclusion of the latter in study design.

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration. To enable genuine characterization of host-microbiota interactions, microbiome research must exchange ratios for counts. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn's disease, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling).

Tumor-associated macrophages constitute a major component of the stroma of solid tumors, encompassing distinct subpopulations with different characteristics and functions. We aimed to identify M2-oriented tumor-supporting macrophages within the tumor microenvironment as indicators of cancer progression and prognosis, using PET imaging. This can be realized by designing 18 F-labeled camelid single-domain antibody fragments (sdAbs) specifically targeting the macrophage mannose receptor (MMR), which has been identified as an important biomarker on this cell population. Methods: Crossreactive anti-MMR sdAbs were generated after immunization of an alpaca with the extracellular domains of both human and mouse MMR. The lead binder was chosen on the basis of comparisons of binding affinity and in vivo pharmacokinetics. The PET tracer 18 F-fluorobenzoate (FB)-anti-MMR sdAb was developed using the prosthetic group N-succinimidyl-4-18 F-fluorobenzoate ( 18 F-SFB), and its biodistribution, tumor-targeting potential, and specificity in terms of macrophage and MMR targeting were evaluated in mouse tumor models. Results: Four sdAbs were selected after affinity screening, but only 2 were found to be cross-reactive for human and mouse MMR. The lead anti-MMR 3.49 sdAb, bearing an affinity of 12 and 1.8 nM for mouse and human MMR, respectively, was chosen for its favorable in vivo biodistribution profile and tumor-targeting capacity. 18 F-FB-anti-MMR 3.49 sdAb was synthesized with a 5%-10% radiochemical yield using an automated and optimized protocol. In vivo biodistribution analyses showed fast clearance via the kidneys and retention in MMRexpressing organs and tumor. The kidney retention of the fluorinated sdAb was 20-fold lower than a 99m Tc-labeled counterpart. Compared with MMR-and C-C chemokine receptor 2-deficient mice, significantly higher uptake was observed in tumors grown in wild-type mice, demonstrating the specificity of the 18 F tracer for MMR and macrophages, respectively. Conclusion: Anti-MMR 3.49 was denoted as the lead cross-reactive MMR-targeting sdAb. 18 F radiosynthesis was optimized, providing an optimal probe for PET imaging of the tumor-promoting macrophage subpopulation in the tumor stroma. Dur ing tumor development, myeloid cells are attracted to the tumor stroma. These infiltrating immune cells are versatile, adopting different activation states in response to a changing microenvironment, leading to subsets of tumor-associated macrophages (TAMs) with specialized functions (1,2). Two main morphologically distinct TAM subsets can be distinguished on the basis of major histocompatibility complex (MHC) class II expression levels in multiple mouse tumor models. Tumor promotion has been linked with an accumulation of M2-oriented MHC II low TAMs in lung and breast carcinoma (3,4). Accordingly, MHC II low TAMs were found to reside primarily in less oxygenated zones, express hypoxia-regulated genes, and facilitate the angiogenic switch (5). Interestingly, the macrophage mannose receptor (MMR, CD206), a typical M2...