An important question is to what extent metabolic fluxes are regulated by gene expression or by metabolic regulation. There are two distinct aspects to this question: (i) the local regulation of the fluxes through the individual steps in the pathway and (ii) the influence of such local regulation on the pathway's flux. We developed regulation analysis so as to address the former aspect for all steps in a pathway. We demonstrate the method for the issue of how Saccharomyces cerevisiae regulates the fluxes through its individual glycolytic and fermentative enzymes when confronted with nutrient starvation. Regulation was dissected quantitatively into (i) changes in maximum enzyme activity (V max, called hierarchical regulation) and (ii) changes in the interaction of the enzyme with the rest of metabolism (called metabolic regulation). Within a single pathway, the regulation of the fluxes through individual steps varied from fully hierarchical to exclusively metabolic. Existing paradigms of flux regulation (such as single-and multisite modulation and exclusively metabolic regulation) were tested for a complete pathway and falsified for a major pathway in an important model organism. We propose a subtler mechanism of flux regulation, with different roles for different enzymes, i.e., ''leader,'' ''follower,'' or ''conservative,'' the latter attempting to hold back the change in flux. This study makes this subtlety, so typical for biological systems, tractable experimentally and invites reformulation of the questions concerning the drives and constraints governing metabolic flux regulation.gene expression and metabolic regulation ͉ glycolysis ͉ regulation analysis ͉ metabolic control analysis T he flux through a metabolic pathway is determined by the activities of its enzymes and by their interactions with other enzymes. Metabolic-flux changes have often been observed in response to environmental or genetic changes. In the yeast Saccharomyces cerevisiae, for example, changes in glycolytic flux have frequently been found to be accompanied by a myriad of changes in glycolytic enzyme activities (e.g., 1, 2, this work) or amounts (3), which varied in magnitude and direction. The complexity of interactions between enzymes translates into a vast possibility space of combinations of enzyme-activity modulations leading to the same flux change. We wondered how the cell actually regulates its fluxes.Among the proposed mechanisms for metabolic-flux changes, the two clearest hypotheses are (i) modulation of single ratelimiting enzymes and (ii) multisite modulation, i.e., simultaneous and proportional modulation of all enzymes in the pathway, thus causing a change in flux while leaving metabolite concentrations unchanged (4). Although single rate-limiting enzymes exist, control of flux is quite often distributed over several enzymes (5). In the latter case, modulation of a single enzyme is likely to be an ineffective mechanism for changing a pathway's flux. Indeed, attempts to correlate flux changes with changes in single enzyme ac...

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A third collaborative exercise on RNA/DNA co-analysis for body fluid identification and STR profiling was organized by the European DNA Profiling Group (EDNAP). Twenty saliva and semen stains, four dilution series (10-0.01 μl saliva, 5-0.01 μl semen) and, optionally, bona fide or mock casework samples of human or non-human origin were analyzed by 20 participating laboratories using an RNA extraction or RNA/DNA co-extraction method. Two novel mRNA multiplexes were used: a saliva triplex (HTN3, STATH and MUC7) and a semen pentaplex (PRM1, PRM2, PSA, SEMG1 and TGM4). The laboratories used different chemistries and instrumentation and a majority (16/20) were able to successfully isolate and detect mRNA in dried stains. The simultaneous extraction of RNA and DNA from individual stains not only permitted a confirmation of the presence of saliva/semen (i.e. tissue/fluid source of origin), but allowed an STR profile of the stain donor to be obtained as well. The method proved to be reproducible and sensitive, with as little as 0.05 μl saliva or semen, using different analysis strategies. Additionally, we demonstrated the ability to positively identify the presence of saliva and semen, as well as obtain high quality DNA profiles, from old and compromised casework samples. The results of this collaborative exercise involving an RNA/DNA co-extraction strategy support the potential use of an mRNA based system for the identification of saliva and semen in forensic casework that is compatible with current DNA analysis methodologies.

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Forensic characterisation of organ tissue generally occurs through histological and immunological assays of limited sensitivity. Here, we explore an alternative approach and examine a total of 41 candidate mRNA markers for their ability to differentiate between brain, lung, liver, skeletal muscle, heart, kidney and skin. Various selection rounds are applied involving 85 organ tissues (36 excised autopsy specimens and 49 frozen tissue sections, with at least ten specimens for each organ type), 20 commercially available RNAs from different human tissues and at least two specimens of blood, saliva, semen, vaginal mucosa, menstrual secretion or touch samples. Finally, 14 markers are regarded tissue-specific and included in an endpoint RT-PCR multiplex together with one general muscle, one blood and one housekeeping marker. This 17-plex is successfully used to analyse a blind test set of 20 specimens including mixtures, and samples derived from stabbing of organ tissues. With the blind test set samples, it is shown that an earlier described interpretation strategy for RNA cell typing results [1] is also effective for tissue inference. As organ-typing is embedded in a procedure of combined DNA/RNA extraction and analysis, both donor and organ type information is derived from the same sample. Some autopsy specimens presented DNA profiles characteristic for degraded DNA. Nevertheless, the organ-typing multiplex could generate full RNA profiles, which is probably due to small sizes of the amplicons. This assay provides a novel tool for analysis of samples from violent crimes.

In agreement with earlier studies, the mRNA levels of the glycerol-producing enzymes as well as their catalytic capacities increased. Qualitatively this induction followed a similar time course to the increase of the glycerol flux. However, a quantitative regulation analysis of the data revealed an initial regulation by metabolism alone. After only a few minutes gene expression came into play, but even after an hour, 80% of the increase in the glycerol flux was explained by metabolic changes in the cell, and 20% by induction of gene expression. This demonstrates that the novel metabolic mechanism is not just a secondary rescue mechanism, but the most important mechanism to regulate the glycerol flux under physiological conditions.