Genetic identification of medullary neurons underlying congenital hypoventilation.

Mutations in the transcription factors encoded by PHOX2B or LBX1 correlate with congenital central hypoventilation disorders. These conditions are typically characterized by pronounced hypoventilation, central apnea, and diminished chemoreflexes, particularly to abnormally high levels of arterial PCO2. The dysfunctional neurons causing these respiratory disorders are largely unknown. Here, we show that distinct, and previously undescribed, sets of medullary neurons coexpressing both transcription factors (dB2 neurons) account for specific respiratory functions and phenotypes seen in congenital hypoventilation. By combining intersectional chemogenetics, intersectional labeling, lineage tracing, and conditional mutagenesis, we uncovered subgroups of dB2 neurons with key functions in (i) respiratory tidal volumes, (ii) the hypercarbic reflex, (iii) neonatal respiratory stability, and (iv) neonatal survival. These data provide functional evidence for the critical role of distinct medullary dB2 neurons in neonatal respiratory physiology. In summary, our work identifies distinct subgroups of dB2 neurons regulating breathing homeostasis, dysfunction of which causes respiratory phenotypes associated with congenital hypoventilation.

L-type CaV1.2 deletion in the cochlea but not in the brainstem reduces noise vulnerability: implication for CaV1.2-mediated control of cochlear BDNF expression.

Voltage-gated L-type Ca(2+) channels (L-VGCCs) like CaV1.2 are assumed to play a crucial role for controlling release of trophic peptides including brain-derived neurotrophic factor (BDNF). In the inner ear of the adult mouse, besides the well-described L-VGCC CaV1.3, CaV1.2 is also expressed. Due to lethality of constitutive CaV1.2 knock-out mice, the function of this ion channel as well as its putative relationship to BDNF in the auditory system is entirely elusive. We recently described that BDNF plays a differential role for inner hair cell (IHC) vesicles release in normal and traumatized condition. To elucidate a presumptive role of CaV1.2 during this process, two tissue-specific conditional mouse lines were generated. To distinguish the impact of CaV1.2 on the cochlea from that on feedback loops from higher auditory centers CaV1.2 was deleted, in one mouse line, under the Pax2 promoter (CaV1.2(Pax2)) leading to a deletion in the spiral ganglion neurons, dorsal cochlear nucleus, and inferior colliculus. In the second mouse line, the Egr2 promoter was used for deleting CaV1.2 (CaV1.2(Egr2)) in auditory brainstem nuclei. In both mouse lines, normal hearing threshold and equal number of IHC release sites were observed. We found a slight reduction of auditory brainstem response wave I amplitudes in the CaV1.2(Pax2) mice, but not in the CaV1.2(Egr2) mice. After noise exposure, CaV1.2(Pax2) mice had less-pronounced hearing loss that correlated with maintenance of ribbons in IHCs and less reduced activity in auditory nerve fibers, as well as in higher brain centers at supra-threshold sound stimulation. As reduced cochlear BDNF mRNA levels were found in CaV1.2(Pax2) mice, we suggest that a CaV1.2-dependent step may participate in triggering part of the beneficial and deteriorating effects of cochlear BDNF in intact systems and during noise exposure through a pathway that is independent of CaV1.2 function in efferent circuits.

Approaching clinical proteomics: current state and future fields of application in cellular proteomics.

Recent developments in proteomics technology offer new opportunities for clinical applications in hospital or specialized laboratories including the identification of novel biomarkers, monitoring of disease, detecting adverse effects of drugs, and environmental hazards. Advanced spectrometry technologies and the development of new protein array formats have brought these analyses to a standard, which now has the potential to be used in clinical diagnostics. Besides standardization of methodologies and distribution of proteomic data into public databases, the nature of the human body fluid proteome with its high dynamic range in protein concentrations, its quantitation problems, and its extreme complexity present enormous challenges. Molecular cell biology (cytomics) with its link to proteomics is a new fast moving scientific field, which addresses functional cell analysis and bioinformatic approaches to search for novel cellular proteomic biomarkers or their release products into body fluids that provide better insight into the enormous biocomplexity of disease processes and are suitable for patient stratification, therapeutic monitoring, and prediction of prognosis. Experience from studies of in vitro diagnostics and especially in clinical chemistry showed that the majority of errors occurs in the preanalytical phase and the setup of the diagnostic strategy. This is also true for clinical proteomics where similar preanalytical variables such as inter- and intra-assay variability due to biological variations or proteolytical activities in the sample will most likely also influence the results of proteomics studies. However, before complex proteomic analysis can be introduced at a broader level into the clinic, standardization of the preanalytical phase including patient preparation, sample collection, sample preparation, sample storage, measurement, and data analysis is another issue which has to be improved. In this report, we discuss the recent advances and applications that fulfill the criteria for clinical proteomics with the focus on cellular proteomics (cytoproteomics) as related to preanalytical and analytical standardization and to quality control measures required for effective implementation of these technologies and analytes into routine laboratory testing to generate novel actionable health information. It will then be crucial to design and carry out clinical studies that can eventually identify novel clinical diagnostic strategies based on these techniques and validate their impact on clinical decision making.

Approaching clinical proteomics: current state and future fields of application in fluid proteomics.

The field of clinical proteomics offers opportunities to identify new disease biomarkers in body fluids, cells and tissues. These biomarkers can be used in clinical applications for diagnosis, stratification of patients for specific treatment, or therapy monitoring. New protein array formats and improved spectrometry technologies have brought these analyses to a level with potential for use in clinical diagnostics. The nature of the human body fluid proteome with its large dynamic range of protein concentrations presents problems with quantitation. The extreme complexity of the proteome in body fluids presents enormous challenges and requires the establishment of standard operating procedures for handling of specimens, increasing sensitivity for detection and bioinformatical tools for distribution of proteomic data into the public domain. From studies of in vitro diagnostics, especially in clinical chemistry, it is evident that most errors occur in the preanalytical phase and during implementation of the diagnostic strategy. This is also true for clinical proteomics, and especially for fluid proteomics because of the multiple pretreatment processes. These processes include depletion of high-abundance proteins from plasma or enrichment processes for urine where biological variation or differences in proteolytic activities in the sample along with preanalytical variables such as inter- and intra-assay variability will likely influence the results of proteomics studies. However, before proteomic analysis can be introduced at a broader level into the clinical setting, standardization of the preanalytical phase including patient preparation, sample collection, sample preparation, sample storage, measurement and data analysis needs to be improved. In this review, we discuss the recent technological advances and applications that fulfil the criteria for clinical proteomics, with the focus on fluid proteomics. These advances relate to preanalytical factors, analytical standardization and quality-control measures required for effective implementation into routine laboratory testing in order to generate clinically useful information. With new disease biomarker candidates, it will be crucial to design and perform clinical studies that can identify novel diagnostic strategies based on these techniques, and to validate their impact on clinical decision-making.