Visualizing Fusome Morphology via Tubulin Immunofluorescence in Drosophila Ovarian Germ Cells.

In many species, oocytes are initially formed by the mitotic divisions of germline stem cells and their differentiating daughters. These progenitor cells are frequently interconnected in structures called cysts, which may function to safeguard oocyte quality. In Drosophila, an essential germline-specific organelle called the fusome helps maintain and coordinate the mitotic divisions of both germline stem cells and cyst cells. The fusome also serves as a useful experimental marker to identify germ cells during their mitotic divisions. Fusomes are cytoplasmic organelles composed of microtubules, endoplasmic reticulum-derived vesicles, and a meshwork of membrane skeleton proteins. The fusome branches as mitotic divisions progress, traversing the intercellular bridges of germline stem cell/cystoblast pairs and cysts. Here, we provide a protocol to visualize fusome morphology in fixed tissue by stabilizing microtubules and immunostaining for α-Tubulin and other protein constituents of the fusome. We identify a variety of fluorophore-tagged proteins that are useful for visualizing the fusome and describe how these might be combined experimentally. Taken together, these tools provide a valuable resource to interrogate the genetic control of germline stem cell function, oocyte selection, and asymmetric division.

Novel roles for RNA binding proteins squid, hephaesteus, and Hrb27C in Drosophila oogenesis.

BACKGROUND: Reproductive capacity in many organisms is maintained by germline stem cells (GSCs). A complex regulatory network influences stem cell fate, including intrinsic factors, local signals, and hormonal and nutritional cues. Posttranscriptional regulatory mechanisms ensure proper cell fate transitions, promoting germ cell differentiation to oocytes. As essential RNA binding proteins with constitutive functions in RNA metabolism, heterogeneous nuclear ribonucleoproteins (hnRNPs) have been implicated in GSC function and axis specification during oocyte development. HnRNPs support biogenesis, localization, maturation, and translation of nascent transcripts. Whether and individual hnRNPs specifically regulate GSC function has yet to be explored. RESULTS: We demonstrate that hnRNPs are expressed in distinct patterns in the Drosophila germarium. We show that three hnRNPs, squid, hephaestus, and Hrb27C are cell-autonomously required in GSCs for their maintenance. Although these hnRNPs do not impact adhesion of GSCs to adjacent cap cells, squid and hephaestus (but not Hrb27C) are necessary for proper bone morphogenetic protein signaling in GSCs. Moreover, Hrb27C promotes proper GSC proliferation, whereas hephaestus promotes cyst division. CONCLUSIONS: We find that hnRNPs are independently and intrinsically required in GSCs for their maintenance in adults. Our results support the model that hnRNPs play unique roles in stem cells essential for their self-renewal and proliferation.

ß-importin Tnpo-SR promotes germline stem cell maintenance and oocyte differentiation in female Drosophila.

Germ cell development requires interplay between factors that balance cell fate and division. Early in their development, germ cells in many organisms divide mitotically with incomplete cytokinesis. Key regulatory events then lead to the specification of mature gametes, marked by the switch to a meiotic cell cycle program. Though the regulation of germ cell proliferation and meiosis are well understood, how these events are coordinated during development remains incompletely described. Originally characterized in their role as nucleo-cytoplasmic shuttling proteins, ß-importins exhibit diverse functions during male and female gametogenesis. Here, we describe novel, distinct roles for the ß-importin, Transportin-Serine/Arginine rich (Tnpo-SR), as a regulator of the mitosis to meiosis transition in the Drosophila ovary. We find that Tnpo-SR is necessary for germline stem cell (GSC) establishment and self-renewal, likely by controlling the response of GSCs to bone morphogenetic proteins. Depletion of Tnpo-SR results in germ cell counting defects and loss of oocyte identity. We show that in the absence of Tnpo-SR, proteins typically suppressed in germ cells when they exit mitosis fail to be down-regulated, and oocyte-specific factors fail to accumulate. Together, these findings provide new insight into the balance between germ cell division and differentiation and identify novel roles for ß-importins in germ cell development.

Treatment of steroid-resistant nephrotic syndrome in the genomic era.

The pathogenesis of steroid-resistant nephrotic syndrome (SRNS) is not completely known. Recent advances in genomics have elucidated some of the molecular mechanisms and pathophysiology of the disease. More than 50 monogenic causes of SRNS have been identified; however, these genes are responsible for only a small fraction of SRNS in outbred populations. There are currently no guidelines for genetic testing in SRNS, but evidence from the literature suggests that testing should be guided by the genetic architecture of the disease in the population. Notably, most genetic forms of SRNS do not respond to current immunosuppressive therapies; however, a small subset of patients with monogenic SRNS will achieve partial or complete remission with specific immunomodulatory agents, presumably due to non-immunosuppressive effects of these agents. We suggest a pragmatic approach to the therapy of genetic SRNS, as there is no evidence-based algorithm for the management of the disease.

Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients.

OBJECTIVE: Personalized medicine merges genetics, physiology, and patient outcome. Loss of physiologic complexity (heart rate [HR] variability) is a bedside biomarker for autonomic nervous system (ANS) dysfunction. We hypothesized that variability in ANS receptor proteins (genetics) and loss of complexity (physiology) are independently associated with mortality in critical illness. SUMMARY BACKGROUND DATA: Decreased HR complexity has been associated with increased mortality and morbidity in trauma and other critically ill populations. Genetic variations in alpha-1A and beta-2 adrenergic receptors (ADRA1A, ADRB2) have been associated with changes in smooth muscle tone in various tissues, and implicated in bronchial hyper-responsiveness, metabolic syndrome, and other disorders. METHODS: A cohort of 644 trauma intensive care unit (ICU) admissions had complexity data and genetic samples. Two ANS receptor polymorphisms (rs1048101, Alpha ADRA1A and rs1042714, Beta ADRB2) were genotyped. Physiologic complexity at various points in the ICU stay was measured using previously-studied integer HR multiscale entropy (MSE) over 6-hour intervals (~21,600 HR data points/interval/patient). Logistic regression assessed the concurrent relationship of genotypes, complexity, and probability of survival, an acuity score incorporating age, injury mechanism/severity, and admission vitals, to risk of death. RESULTS: Of total, 96 patients (15%) died. Nonsurvivors had lower complexity at early, middle, and late portions of ICU stay (median MSE at least 25% less in nonsurvivors, P < 0.001) and lower incidence of the GG ADRB2 genotype (7.5% vs. 18.3%, P < 0.001). In multivariable logistic regression, the GG ADRB2 genotype carried ~3-fold decrease in mortality odds (odd ratio [OR] = 0.33, P = 0.01), independent of significant effects in HR MSE (OR = 0.93, P < 0.001), and probability of survival (OR = 0.22, P < 0.001). CONCLUSIONS: This first study to simultaneously examine ANS genetics, the biomarker complexity, and mortality concludes: (1) ANS genetics and physiologic complexity are independently related to mortality; (2) Genetics and complexity add information over traditional acuity scoring (probability of survival); and (3) Simultaneous assessment of ANS physiology and genetics may yield novel research, diagnostic, and therapeutic opportunities in critical illness.

Genetic variation in the autonomic nervous system affects mortality: a study of 1,095 trauma patients.

BACKGROUND: We have previously demonstrated an unappreciated link between the autonomic nervous system and mortality, heart rate variability, and physiologic complexity. STUDY DESIGN: Genetic variation in adrenergic receptors or key enzymes in catecholamine degradation could be associated with, and potentially explain, autonomic nervous system dysfunction and its impact on mortality after severe trauma. Three genetic polymorphisms critical to the adrenergic pathway were evaluated: beta-2 adrenergic receptor (ADBR2: Q27E), alpha-1a adrenergic receptor (ADRA1A:R347C), and catechol-O-methyl transferase (COMT: V158M). The study population consisted of 1,095 trauma admissions between April 2005 and April 2007. These patients all had genotyping performed using mass spectrometric analysis (Sequenom, Inc). The genetic data were linked with detailed demographic and clinical data. Trauma Related Injury Severity Score (TRISS) probability of survival was used as a composite measure of injury severity, admission physiology, and demographic factors in the multivariate logistic regression analyses of mortality outcomes data. RESULTS: The overall mortality rate for the study population was 14.2% (155 of 1,095). Univariate comparisons of genotypes with mortality revealed a significant association with the ADBR2 polymorphism: CC=15.9%, GC=14.8% and GG=7.6%, p=0.02. The apparently protective ADBR2 GG genotype was seen in 15.5% (170 of 1,095) of the study population. In multivariate analysis, which included adjustment for TRISS, the ADBR2 GG genotype was associated with reduced mortality (odds ratio 0.36, p=0.002). CONCLUSIONS: Genetic variation in the beta-2 adrenergic receptor (ADBR2:Q27E) associated with bronchial constriction appears protective (odds ratio 0.36), perhaps by making the receptor resistant to downregulation. These genetic data support the emerging understanding of critical role of the autonomic nervous system in the response to injury.

Genetic variation in complement component 2 of the classical complement pathway is associated with increased mortality and infection: a study of 627 patients with trauma.

BACKGROUND: Trauma is a disease of inflammation. Complement Component 2 (C2) is a protease involved in activation of complement through the classical pathway and has been implicated in a variety of chronic inflammatory diseases. We hypothesized that genetic variation in C2 (E318D) identifies a high-risk subgroup of patients with trauma reflecting increased mortality and infection (ventilator-associated pneumonia [VAP]). Consequently, genetic variation in C2 may stratify patient risk and illuminate underlying mechanisms for therapeutic intervention. METHODS: DNA samples from 702 patients with trauma were genotyped for C2 E318D and linked with covariates (age: mean 42.8 years, gender: 74% male, ethnicity: 80% white, mechanism: 84% blunt, injury severity score: mean 25.0, admission lactate: mean 3.13 mEq/L) and outcomes: mortality 9.9% and VAP: 18.5%. VAP was defined by quantitative bronchoalveolar lavage (> 10). Multivariate regression analysis determined the relationship of genotype and covariates to risk of death and VAP. However, patients with injury severity score > or = 45 were excluded from the multivariate analysis, as magnitude of injury overwhelms genetics and covariates in determining outcome. RESULTS: Fifty-two patients (8.3%) had the high-risk heterozygous genotype, associated with a significant increase in mortality and VAP. CONCLUSION: In 702 patients with trauma, 8.3% had a high-risk genetic variation in C2 associated with increased mortality (odds ratio = 2.65) and infection (odds ratio = 2.00). This variation: (1) identifies a previously unknown high-risk group for infection and mortality; (2) can be determined at admission; (3) may provide opportunity for early therapeutic intervention; and (4) requires validation in a distinct cohort of patients.

Cardiac uncoupling and heart rate variability are associated with intracranial hypertension and mortality: a study of 145 trauma patients with continuous monitoring.

BACKGROUND: A noninvasive tool reflecting intracranial hypertension (ICH) should prompt early invasive monitoring and reduce secondary injury after traumatic brain injury. We hypothesized that integer heart rate variability (HRV) may be associated with rises in intracranial pressure (ICP); changes in HRV may precede changes in ICP; and both increases in ICP and cardiac uncoupling (low HRV) predict mortality. METHODS: Of 14,330 consecutive trauma admissions, 291 of these patients had an injury requiring intracranial monitoring. Of these patients 145 had simultaneous HRV and ICP monitoring with a Camino monitor. ICP and heart rate (HR) data were matched and divided into 5-minute intervals (N = 117,956, representing 24.4 million HR and ICP data points). In each interval, the median ICP, and SD of HR (HRSD5) were calculated. Cardiac uncoupling was defined as an interval with HRSD5 between 0.3 bpm and 0.6 bpm. Cardiac uncoupling was compared between ICP categories using the Wilcoxon Rank-Sum test, and logistic regression was used to assess the continuous relationship between ICP and risk of uncoupling. RESULTS: Cardiac uncoupling increases as ICP increases (p < 0.001). Uncoupling nearly doubles when comparing acceptable ICP (<20 mm Hg, 11% uncoupled) to ICH (31-50 mm Hg, 18% uncoupled), with uncoupling = 13% in the intermediate group (ICP 21-30 mm Hg). This trend continues at the level of malignant ICH (>50 mm Hg, 22% uncoupled). CONCLUSION: Cardiac uncoupling increases as ICP increases. Both cardiac uncoupling and ICH predict mortality. Cardiac uncoupling may precede ICH but is not yet an indication for invasive monitoring.

Heart rate multiscale entropy at three hours predicts hospital mortality in 3,154 trauma patients.

Complexity is a measure of variation and randomness potentially indicating improvement or deterioration in critically ill patients. Previously, we have shown integer heart rate (HR) multiscale entropy (MSE), an indicator of complexity, predicts death based on long duration (12 h) and dense (>or=0.4 Hz) windows of HR data. However, such restrictions reduce the use of MSE in the clinical setting. We hypothesized MSE predicts death using HR data of shorter duration and lower density. During the initial 24 h of intensive care unit stay, 3,154 patients had at least 3 h of continuous integer HR sampled. The first continuous window of 3, 6, 9, and 12 h was selected for each patient regardless of density, and an open-source MSE algorithm was applied (M. Costa, www.physionet.org; m = 2; r = 0.15). Risk of death based on MSE, alone and with covariates (age, sex, injury severity score), was assessed using randomly selected logistic regression in half of the cases. Area under the receiver operator curve (AUC) was computed in the other half in subgroups having various durations and densities of HR data. At days 2.3 (median) and 4.9 (mean), 441 patients (14%) died. Multiscale entropy stratified patients by mortality and was an independent predictor of death using 3 h or more of data. Multiscale entropy alone (AUC = 0.66 - 0.71) predicted death comparably to covariates alone (AUC = 0.72). We conclude: (1) Heart rate MSE within hours of admission predicts death occurring days later. (2) Multiscale entropy is robust to variation in bedside data duration and density occurring in a working intensive care unit. (3) Complexity may be a new clinical biomarker of outcome.

Reduced heart rate variability: an indicator of cardiac uncoupling and diminished physiologic reserve in 1,425 trauma patients.

BACKGROUND: Measurements of a patient's physiologic reserve (age, injury severity, admission lactic acidosis, transfusion requirements, and coagulopathy) reflect robustness of response to surgical insult. We have previously shown that cardiac uncoupling (reduced heart rate variability, HRV) in the first 24 hours after injury correlates with mortality and autonomic nervous system failure. We hypothesized: Deteriorating physiologic reserve correlates with reduced HRV and cardiac uncoupling. METHODS: There were 1,425 trauma ICU patients that satisfied the inclusion criteria. Differences in mortality across categorical measurements of the domains of physiologic reserve were assessed using the chi test. The relationship of cardiac uncoupling and physiologic reserve was examined using multivariate logistic regression models for various levels of cardiac uncoupling (>0 through 28% reduced HRV in the first 24 hours). RESULTS: Of these, 797 (55.9%) patients exhibited cardiac uncoupling. Deteriorating measures of physiologic reserve reflected increased risk of death. Measures of acidosis (admission lactate, time to lactate normalization, and lactate deterioration over the first 24 hours), coagulopathy, age, and injury severity contributed significantly to the risk of cardiac uncoupling (area under receiver operator curve, ROC=0.73). The association between deteriorating reserve and cardiac uncoupling increases with the threshold for uncoupling (ROC=0.78). CONCLUSIONS: Reduced heart rate variability is a new biomarker reflecting the loss of command and control of the heart (cardiac uncoupling). Risk of cardiac uncoupling increases significantly as a patient's physiologic reserve deteriorates and physiologic exhaustion approaches. Cardiac uncoupling provides a noninvasive, overall measure of a patient's clinical trajectory over the first 24 hours of ICU stay.

Cardiac uncoupling and heart rate variability stratify ICU patients by mortality: a study of 2088 trauma patients.

OBJECTIVE: We have previously shown that cardiac uncoupling (reduced heart rate variability) in the first 24 hours of trauma ICU stay is a robust predictor of mortality. We hypothesize that cardiac uncoupling over the entire ICU stay independently predicts mortality, reveals patterns of injury, and heralds complications. METHODS: A total of 2088 trauma ICU patients satisfied the inclusion criteria for this study. Cardiac uncoupling by outcome was compared using the Wilcoxon rank sum test. Risk of death from cardiac uncoupling and covariates (age, ISS, AIS Head Score, total transfusion requirements) was assessed using multivariate logistic regression models at each ICU day. Univariate logistic regression was used to assess risk of death from uncoupling irrespective of covariates at each ICU day. RESULTS: A total of 1325 (63.5%) patients displayed some degree of uncoupling over their ICU stay. The difference in uncoupling between survivors and nonsurvivors is both dramatic and consistent across the entire ICU stay, indicating that the presence of uncoupling is unrelated to the cause of death. However, the magnitude of uncoupling varies by day when data is stratified by cause of death. CONCLUSIONS: Cardiac uncoupling: 1) is an independent predictor of death throughout the ICU stay, 2) has a predictive window of 2 to 4 days, and 3) appears to increase in response to inflammation, infection, and multiple organ failure.

Heart rate variability predicts trauma patient outcome as early as 12 h: implications for military and civilian triage.

BACKGROUND: Our previous work demonstrated dense physiological data capture in the intensive care unit (ICU), defined a new vital sign Cardiac Volatility Related Dysfunction (CVRD) reflecting reduced heart rate variability, and demonstrated CVRD predicts death during the hospital stay adjusting for age and injury severity score (ISS). We hypothesized a more precise definition of variability in integer heart rate improves predictive power earlier in ICU stay, without adjusting for covariates. METHODS: Approximately 120 million integer heart rate (HR) data points were prospectively collected and archived from 1316 trauma ICU patients, linked to outcome data, and de-identified. HR standard deviation was computed in each 5-min interval (HR(SD5)). HR(SD5) logistic regression identified ranges predictive of death. The study group was randomly divided. Integer heart rate variability (% time HR(SD5) in predictive distribution ranges) models were developed on the first set (N = 658) at 1, 2, 4, 6, 8, 12, and 24 h after ICU admission, and validated on the second set (N = 658). RESULTS: HR(SD5) is bimodal, predicts death at low (0.1-0.9 bpm) and survival at high (1.8-2.6 bpm) ranges. HRV predicts death as early as 12 h (ROC = 0.67). HRV in a moving 1-h window is a simple graphic display technique. CONCLUSIONS: Dense physiological data capture allows calculation of HRV, which: 1) Independently predicts hospital death in trauma patients at 12 h; 2) Shows early differences by mortality in groups of patients when viewed in a moving window; and 3) May have implications for military and civilian triage.