An objective function exploiting suboptimal solutions in metabolic networks

Background: Flux Balance Analysis is a theoretically elegant, computationally efficient, genome-scale approach to predicting biochemical reaction fluxes. Yet FBA models exhibit persistent mathematical degeneracy that generally limits their predictive power. Results: We propose a novel objective function for cellular metabolism that accounts for and exploits degeneracy in the metabolic network to improve flux predictions. In our model, regulation drives metabolism toward a region of flux space that allows nearly optimal growth. Metabolic mutants deviate minimally from this region, a function represented mathematically as a convex cone. Near-optimal flux configurations within this region are considered equally plausible and not subject to further optimizing regulation. Consistent with relaxed regulation near optimality, we find that the size of the near-optimal region predicts flux variability under experimental perturbation. Conclusion: Accounting for suboptimal solutions can improve the predictive power of metabolic FBA models. Because fluctuations of enzyme and metabolite levels are inevitable, tolerance for suboptimality may support a functionally robust metabolic network

Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures

Advances in sequencing have enabled the identification of mutations acquired by bacterial pathogens during infection1-10. However, it remains unclear whether adaptive mutations fix in the population or lead to pathogen diversification within the patient11,12. Here, we study the genotypic diversity of Burkholderia dolosa within people with cystic fibrosis by re-sequencing individual colonies and whole populations from single sputum samples. Extensive intra-sample diversity reveals that mutations rarely fix within a patient's pathogen population—instead, diversifying lineages coexist for many years. When strong selection is acting on a gene, multiple adaptive mutations arise but neither sweeps to fixation, generating lasting allele diversity that provides a recorded signature of past selection. Genes involved in outer-membrane components, iron scavenging and antibiotic resistance all showed this signature of within-patient selection. These results offer a general and rapid approach for identifying selective pressures acting on a pathogen in individual patients based on single clinical samples

Towards a Synthetic Chloroplast

The evolution of eukaryotic cells is widely agreed to have proceeded through a series of endosymbiotic events between larger cells and proteobacteria or cyanobacteria, leading to the formation of mitochondria or chloroplasts, respectively. Engineered endosymbiotic relationships between different species of cells are a valuable tool for synthetic biology, where engineered pathways based on two species could take advantage of the unique abilities of each mutualistic partner.We explored the possibility of using the photosynthetic bacterium Synechococcus elongatus PCC 7942 as a platform for studying evolutionary dynamics and for designing two-species synthetic biological systems. We observed that the cyanobacteria were relatively harmless to eukaryotic host cells compared to Escherichia coli when injected into the embryos of zebrafish, Danio rerio, or taken up by mammalian macrophages. In addition, when engineered with invasin from Yersinia pestis and listeriolysin O from Listeria monocytogenes, S. elongatus was able to invade cultured mammalian cells and divide inside macrophages.Our results show that it is possible to engineer photosynthetic bacteria to invade the cytoplasm of mammalian cells for further engineering and applications in synthetic biology. Engineered invasive but non-pathogenic or immunogenic photosynthetic bacteria have great potential as synthetic biological devices

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Cutaneous Surgical Wounds Have Distinct Microbiomes from Intact Skin

Commensal bacteria on skin may limit the ability of pathogenic bacteria to cause clinically significant infections. The bacteria on healing acute wounds, which might provide such a protective effect, have not been described using culture-independent approaches in the absence of antibiotics.</jats:p

Correspondence between BioAnalyzer traces and the length distribution of aligned reads.

<p>Panels A-C show three representative BioAnalyzer traces from three sample preparations of <i>S</i>. <i>maltophilia</i>. Panels D-F show the corresponding estimated fragment-size distributions (black) and the actual distributions of fragment lengths imputed from alignment to the reference genome (blue). A BioAnalyzer trace <i>f(x)</i> shows fluorescence <i>f</i> at fragment length <i>x</i>. However, we are interested in <i>n(x)</i>, the (relative) number of fragments <i>n</i> of length <i>x</i>. Since fluorescence of a DNA fragment is proportional to its length, <i>n(x)</i> ∝ <i>f(x) / x</i>. Note that sequencing can be successful despite the presence of apparently very long fragments (which are likely heteroduplexes) in the BioAnalyzer traces (Panels C and F).</p

Distribution of the fraction of unique reads over 261 <i>E</i>. <i>coli</i> samples.

<p>Samples had between 0.2 and 2.8 million reads with 90% of samples having over 1 million reads. Raw reads were filtered and then aligned to a reference genome using bowtie2. Unique reads are those that appear only once in the alignment for a particular sample. These are the reads that remain after use of the rmdup tool in samtools. Non-unique reads arise primarily when the same tagmented fragment is amplified during PCR. A low fraction of non-unique reads implies a diversity of fragments after tagmentation, and that errors introduced during PCR will not reach high frequencies.</p

<i>S. elongatus</i> can grow inside the macrophage cytoplasm.

<p>A.) Time lapse microscopy of macrophages infected with +inv+llo <i>S. elongatus</i> kept in the dark shows the gradual decrease in red autofluorescence over the course of 12 hours. In contrast, when kept in the light, B.) empty vector <i>S. elongatus</i> autofluorescence is observed to gradually decrease over the course of several days (top row), while a significant increase in red <i>S. elongatus</i> autofluorescence was observed in macrophages infected with inv llo <i>S. elongatus</i> for two days post-infection (bottom row). This fluorescence was observed to decrease after the third day of infection. C.) This change in fluorescence over time can be quantified as a change in background subtracted mean fluorescence in ImageJ and averaged over triplicate experiments. Empty vector (blue line) and +inv+llo <i>S. elongatus</i> (red line) show marked differences in growth when infected at similar densities of 1–2 bacterial cells per macrophage. D.) +inv+llo <i>S. elongatus</i> displayed infection density dependent growth rates in macrophages. Each line shows change in mean fluorescence in cells infected at a single starting density, ranging in multiples of two from fewer than one cell per macrophage to approximately 4 bacteria per macrophage. E.) Macrophage cell counts were variable across replicates and over the course of the experiment but displayed no significant difference between macrophages infected with empty vector <i>S. elongatus</i> at low (green line) or high density (blue line), or +inv+llo <i>S. elongatus</i> at low (red line) or high (yellow line) density. F.) When infected at low density of fewer than one bacteria per macrophage, <i>S. elongatus</i> division was observed during 18 hour time-lapse fluorescent microscopy in approximately 1% of macrophages observed, in particular those cells that contained more than one bacterial cell due to stochastic fluctuations.</p