Estimating cladoceran birth rate: use of the egg age distribution to estimate mortality of ovigerous females and eggs

The birth rate of natural cladoceran populations can change rapidly (during 2–3 days), reflecting rapid changes in their environment. If the egg ratio is calculated on the basis of egg age distribution, the birth rate can be estimated at short sampling intervals (shorter than egg stage duration) by modified Paloheimo's (1974) formula. When female size structure and age of eggs in clutches at the beginning and the end of a sampling interval are known, death rates of ovigerous females and eggs in separate size classes can be determined and incorporated in birth rate estimates. All these methods have been employed using the data on the population of Diaphanosoma brahyurum from the lake Obsterno (North-Western Belarus) in July–August, 1992. The birth rate values computed by the proposed methods and Poloheimo's formula differed significantly in many cases. The accuracy of birth rate estimations from various calculation methods was tested using a computer simulation. The model contains the essential features of cladoceran life history: distinct egg, juvenile and adult stages, development of eggs and reproduction. The population was divided into 25 age classes, each of 1 day duration. Durations of the egg, juvenile and adult stages were set at 3, 6 and 20 days, respectively. The embryogenesis was divided into three egg stages, each of 1 day duration. Survivorship was set from 0.2 up to 1.0 for each age class. The survivorship and brood size were changed through each of five time intervals (days) that allowed to simulate an increase or reduction of population density. Fecundity, survivorship and egg stage duration remained constant during each of 5 days that assumed stability of an environment (this does not occur in nature). Nevertheless, the egg ratio, proportion of juveniles and birth rates were variable even under these circumstances. Computer simulations showed that Poloheimo's formula evaluates birth rate with the relative error of 62% and usually overestimates its values. We propose methods to decrease errors of birth rate estimations by 3.5–5.5 times.     

The Effect of Leaf Age on Gas Exchange and Malate Accumulation in C3-CAM Plant Marrubium Frivaldszkyanum (Lamiaceae)

For the first time the expression of C₃ and CAM in the leaves of different age of Marrubium frivaldszkyanum Boiss, is reported. With increasing leaf age a typical C₃ photosynthesis pattern and high transpiration rate were found. In older leaves a shift to CAM occurred and the 24-h transpiration water loss decreased. A correlation was established between leaf area and accumulation of malate. Water loss at early stages of leaf expansion may be connected with the shift to CAM and the water economy of the whole plant.     

Glycoproteomics Landscape of Asymptomatic and Symptomatic Human Alzheimer’s Disease Brain

Molecular changes in the brain of individuals afflicted with Alzheimer's disease (AD) are an intense area of study. Little is known about the role of protein abundance and posttranslational modifications in AD progression and treatment, in particular large-scale intact N-linked glycoproteomics analysis. To elucidate the N-glycoproteome landscape, we developed an approach based on multi-lectin affinity enrichment, hydrophilic interaction chromatography, and LC-MS–based glycoproteomics. We analyzed brain tissue from 10 persons with no cognitive impairment or AD, 10 with asymptomatic AD, and 10 with symptomatic AD, detecting over 300 glycoproteins and 1900 glycoforms across the samples. The majority of glycoproteins have N-glycans that are high-mannosidic or complex chains that are fucosylated and bisected. The Man5 N-glycan was found to occur most frequently at >20% of the total glycoforms. Unlike the glycoproteomes of other tissues, sialylation is a minor feature of the brain N-glycoproteome, occurring at <9% among the glycoforms. We observed AD-associated differences in the number of antennae, frequency of fucosylation, bisection, and other monosaccharides at individual glycosylation sites among samples from our three groups. Further analysis revealed glycosylation differences in subcellular compartments across disease stage, including glycoproteins in the lysosome frequently modified with paucimannosidic glycans. These results illustrate the N-glycoproteomics landscape across the spectrum of AD clinical and pathologic severity and will facilitate a deeper understanding of progression and treatment development.     

Phosphoproteome Profiling of the Receptor Tyrosine Kinase MuSK Identifies Tyrosine Phosphorylation of Rab GTPases

Muscle-specific receptor tyrosine kinase (MuSK) agonist antibodies were developed 2 decades ago to explore the benefits of receptor activation at the neuromuscular junction. Unlike agrin, the endogenous agonist of MuSK, agonist antibodies function independently of its coreceptor low-density lipoprotein receptor–related protein 4 to delay the onset of muscle denervation in mouse models of ALS. Here, we performed dose–response and time-course experiments on myotubes to systematically compare site-specific phosphorylation downstream of each agonist. Remarkably, both agonists elicited similar intracellular responses at known and newly identified MuSK signaling components. Among these was inducible tyrosine phosphorylation of multiple Rab GTPases that was blocked by MuSK inhibition. Importantly, mutation of this site in Rab10 disrupts association with its effector proteins, molecule interacting with CasL 1/3. Together, these data provide in-depth characterization of MuSK signaling, describe two novel MuSK inhibitors, and expose phosphorylation of Rab GTPases downstream of receptor tyrosine kinase activation in myotubes.     

MicroID2: A Novel Biotin Ligase Enables Rapid Proximity-Dependent Proteomics

Identifying protein–protein and other proximal interactions is central to dissecting signaling and regulatory processes in cells. BioID is a proximity-dependent biotinylation method that uses an “abortive” biotin ligase to detect proximal interactions in cells in a highly reproducible manner. Recent advancements in proximity-dependent biotinylation tools have improved efficiency and timing of labeling, allowing for measurement of interactions on a cellular timescale. However, issues of size, stability, and background labeling of these constructs persist. Here we modified the structure of BioID2, derived from Aquifex aeolicus BirA, to create a smaller, highly active, biotin ligase that we named MicroID2. Truncation of the C terrminus of BioID2 and addition of mutations to alleviate blockage of biotin/ATP binding at the active site of BioID2 resulted in a smaller and highly active construct with lower background labeling. Several additional point mutations improved the function of our modified MicroID2 construct compared with BioID2 and other biotin ligases, including TurboID and miniTurbo. MicroID2 is the smallest biotin ligase reported so far (180 amino acids [AAs] for MicroID2 versus 257 AAs for miniTurbo and 338 AAs for TurboID), yet it demonstrates only slightly less labeling activity than TurboID and outperforms miniTurbo. MicroID2 also had lower background labeling than TurboID. For experiments where precise temporal control of labeling is essential, we in addition developed a MicroID2 mutant, termed lbMicroID2 (low background MicroID2), that has lower labeling efficiency but significantly reduced biotin scavenging compared with BioID2. Finally, we demonstrate utility of MicroID2 in mass spectrometry experiments by localizing MicroID2 constructs to subcellular organelles and measuring proximal interactions.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Targeting age‐specific changes in CD4+ T cell metabolism ameliorates alloimmune responses and prolongs graft survival

Age impacts alloimmunity. Effects of aging on T‐cell metabolism and the potential to interfere with immunosuppressants have not been explored yet. Here, we dissected metabolic pathways of CD4⁺ and CD8⁺ T cells in aging and offer novel immunosuppressive targets. Upon activation, CD4⁺ T cells from old mice failed to exhibit adequate metabolic reprogramming resulting into compromised metabolic pathways, including oxidative phosphorylation (OXPHOS) and glycolysis. Comparable results were also observed in elderly human patients. Although glutaminolysis remained the dominant and age‐independent source of mitochondria for activated CD4⁺ T cells, old but not young CD4⁺ T cells relied heavily on glutaminolysis. Treating young and old murine and human CD4⁺ T cells with 6‐diazo‐5‐oxo‐l‐norleucine (DON), a glutaminolysis inhibitor resulted in significantly reduced IFN‐γ production and compromised proliferative capacities specifically of old CD4⁺ T cells. Of translational relevance, old and young mice that had been transplanted with fully mismatched skin grafts and treated with DON demonstrated dampened Th1‐ and Th17‐driven alloimmune responses. Moreover, DON diminished cytokine production and proliferation of old CD4⁺ T cells in vivo leading to a significantly prolonged allograft survival specifically in old recipients. Graft prolongation in young animals, in contrast, was only achieved when DON was applied in combination with an inhibition of glycolysis (2‐deoxy‐d‐glucose, 2‐DG) and OXPHOS (metformin), two alternative metabolic pathways. Notably, metabolic treatment had not been linked to toxicities. Remarkably, immunosuppressive capacities of DON were specific to CD4⁺ T cells as adoptively transferred young CD4⁺ T cells prevented immunosuppressive capacities of DON on allograft survival in old recipients. Depletion of CD8⁺ T cells did not alter transplant outcomes in either young or old recipients. Taken together, our data introduce an age‐specific metabolic reprogramming of CD4⁺ T cells. Targeting those pathways offers novel and age‐specific approaches for immunosuppression.     

Body condition helps to explain metabolic rate variation in wolf spiders

1. Metabolism is the fundamental process that powers life. Understanding what drives metabolism is therefore critical to our understanding of the ecology and behaviour of organisms in nature. 2. Metabolic rate generally scales with body size according to a power law. However, considerable unexplained variation in metabolic rate remains after accounting for body mass with scaling functions. 3. We measured resting metabolic rates (oxygen consumption) of 227 field‐caught wolf spiders. Then, we tested for effects of body mass, species, and body condition on metabolic rate. 4. Metabolic rate scales with body mass to the 0.85 power in these wolf spiders, and there are metabolic rate differences between species. After accounting for these factors, residual variation in metabolic rate is related to spider body condition (abdomen:cephalothorax ratio). Spiders with better body condition consume more oxygen. 5. These results indicate that recent foraging history is an important determinant of metabolic rate, suggesting that although body mass and taxonomic identity are important, other factors can provide helpful insights into metabolic rate variation in ecological communities.