Intracellular bacterial pathogens can exhibit large heterogeneity in growth rate inside host cells, with major consequences for the infection outcome. If and how the host responds to this heterogeneity remains poorly understood. Here, we combined a fluorescent reporter of bacterial cell division with single-cell RNA-sequencing analysis to study the macrophage response to different intracellular states of the model pathogen Salmonella enterica serovar Typhimurium. The transcriptomes of individual infected macrophages revealed a spectrum of functional host response states to growing and non-growing bacteria. Intriguingly, macrophages harbouring non-growing Salmonella display hallmarks of the proinflammatory M1 polarization state and differ little from bystander cells, suggesting that non-growing bacteria evade recognition by intracellular immune receptors. By contrast, macrophages containing growing bacteria have turned into an anti-inflammatory, M2-like state, as if fast-growing intracellular Salmonella overcome host defence by reprogramming macrophage polarization. Additionally, our clustering approach reveals intermediate host functional states between these extremes. Altogether, our data suggest that gene expression variability in infected host cells shapes different cellular environments, some of which may favour a growth arrest of Salmonella facilitating immune evasion and the establishment of a long-term niche, while others allow Salmonella to escape intracellular antimicrobial activity and proliferate.

Most RNAs within polarized cells such as neurons are sorted subcellularly in a coordinated manner. Despite advances in the development of methods for profiling polyadenylated RNAs from small amounts of input RNA, techniques for profiling coding and non-coding RNAs simultaneously are not well established. Here, we optimized a transcriptome profiling method based on double-random priming and applied it to serially diluted total RNA down to 10 pg. Read counts of expressed genes were robustly correlated between replicates, indicating that the method is both reproducible and scalable. Our transcriptome profiling method detected both coding and long non-coding RNAs sized >300 bases. Compared to total RNAseq using a conventional approach our protocol detected 70% more genes due to reduced capture of ribosomal RNAs. We used our method to analyze the RNA composition of compartmentalized motoneurons. The somatodendritic compartment was enriched for transcripts with post-synaptic functions as well as for certain nuclear non-coding RNAs such as 7SK. In axons, transcripts related to translation were enriched including the cytoplasmic non-coding RNA 7SL. Our profiling method can be applied to a wide range of investigations including perturbations of subcellular transcriptomes in neurodegenerative diseases and investigations of microdissected tissue samples such as anatomically defined fiber tracts.

Context: Alterations in the cAMP signaling pathway are common in hormonally active endocrine tumors. Somatic mutations atGNASare causative in 30–40% of GH-secreting adenomas. Recently, mutations affecting theUSP8andPRKACAgene have been reported in ACTH-secreting pituitary adenomas and cortisol-secreting adrenocortical adenomas respectively. However, the pathogenesis of many GH-secreting adenomas remains unclear.Aim: Comprehensive genetic characterization of sporadic GH-secreting adenomas and identification of new driver mutations.Design: Screening for somatic mutations was performed in 67 GH-secreting adenomas by targeted sequencing forGNAS,PRKACA, andUSP8mutations (n=31) and next-generation exome sequencing (n=36).Results: By targeted sequencing, known activating mutations inGNASwere detected in five cases (16.1%), while no somatic mutations were observed in bothPRKACAandUSP8. Whole-exome sequencing identified 132 protein-altering somatic mutations in 31/36 tumors with a median of three mutations per sample (range: 1–13). The only recurrent mutations have been observed inGNAS(31.4% of cases). However, seven genes involved in cAMP signaling pathway were affected in 14 of 36 samples and eight samples harbored variants in genes involved in the calcium signaling or metabolism. At the enrichment analysis, several altered genes resulted to be associated with developmental processes. No significant correlation between genetic alterations and the clinical data was observed.Conclusion: This study provides a comprehensive analysis of somatic mutations in a large series of GH-secreting adenomas. No novel recurrent genetic alterations have been observed, but the data suggest that beside cAMP pathway, calcium signaling might be involved in the pathogenesis of these tumors.

Context Adrenocortical carcinoma (ACC) has a heterogeneous prognosis, and current medical therapies have limited efficacy in its advanced stages. Genome-wide multiomics studies identified molecular patterns associated with clinical outcome. Objective Here, we aimed at identifying a molecular signature useful for both personalized prognostic stratification and druggable targets, using methods applicable in clinical routine. Design In total, 117 tumor samples from 107 patients with ACC were analyzed. Targeted next-generation sequencing of 160 genes and pyrosequencing of 4 genes were applied to formalin-fixed, paraffin-embedded (FFPE) specimens to detect point mutations, copy number alterations, and promoter region methylation. Molecular results were combined with clinical/histopathological parameters (tumor stage, age, symptoms, resection status, and Ki-67) to predict progression-free survival (PFS). Results In addition to known driver mutations, we detected recurrent alterations in genes not previously associated with ACC (e.g., NOTCH1, CIC, KDM6A, BRCA1, BRCA2). Best prediction of PFS was obtained integrating molecular results (more than one somatic mutation, alterations in Wnt/β-catenin and p53 pathways, high methylation pattern) and clinical/histopathological parameters into a combined score (P < 0.0001, χ² = 68.6). Accuracy of prediction for early disease progress was 83.3% (area under the receiver operating characteristic curve: 0.872, 95% confidence interval 0.80 to 0.94). Furthermore, 17 potentially targetable alterations were found in 64 patients (e.g., in CDK4, NOTCH1, NF1, MDM2, and EGFR and in DNA repair system). Conclusions This study demonstrates that molecular profiling of FFPE tumor samples improves prognostication of ACC beyond clinical/histopathological parameters and identifies new potential drug targets. These findings pave the way to precision medicine in this rare disease.