蛋白质预算：合成生物学的成本标尺

合成生物学以创建人工生命体系为目的.实践中人们希望人工生命体系具有更强的生产能力、转化能力、环境适应与监测能力,从而获得更优质的生产方式.生命体系的优化涉及到多层次的调控网络,而根本上还是对细胞中蛋白质的含量、定位、活性的控制.在蛋白质表达水平上进行控制是合成生物学元件设计、模块组装以及适配性研究最核心的手段.类似于工厂中的成本计算,合成生物学创建的人工生命体系(人工细胞工厂)以蛋白质预算为依据.优化蛋白质预算的研究策略已经成功应用于合成生物学研究实践中.     

Operational flexibility quantification in a make-to-order assembly system

Manufacturing flexibility is becoming a fundamental production objective, along with cost, quality, and delivery time. Current production systems face quick changes in market conditions and they need to adapt in this environment. The supply chain and industrial globalization give an important role for assembly systems. Placed at the end of the value chain, assembly systems must face those quick changes successfully to reach the expected performance. The key performance indicators are normally based on cost, quality, and delivery time objectives. Reducing costs and improving quality are almost universal goals. Delivery time is typically determined by customer demand in the supply chain, planning from make-to-stock to make-to-order, and aspiring to reach a just-in-time manufacturing system. In this context, flexibility could be the differential advantage to tackle uncertainty. Closely related to the rest of production objectives and the overall performance of the system, flexibility must be integrated in the system for successful decision-making in operations. This work presents this approach of flexibility. A brief review of flexibility concepts and measurements in the literature precedes an introduction to flexibility, defined based on the function of utility. This function represents the expectations of system performance. This approach allows the formulation of the taxonomy of operational flexibility in agreement with the classical types identified in former works. Next, an integer model is programmed to simulate the basic behavior of task planning in a make-to-order assembly system. This first application illustrates flexibility quantification based on utility evolution. The use of common industrial parameters to quantify operational flexibility will finally facilitate an integrated interpretation of system performance trends.     

Optimal harvesting of a logistic population in an environment with stochastic jumps

Dynamic programming is employed to examine the effects of large, sudden changes in population size on the optimal harvest strategy of an exploited resource population. These changes are either adverse or favorable and are assumed to occur at times of events of a Poisson process. The amplitude of these jumps is assumed to be density independent. In between the jumps the population is assumed to grow logistically. The Bellman equation for the optimal discounted present value is solved numerically and the optimal feedback control computed for the random jump model. The results are compared to the corresponding results for the quasi-deterministic approximation. In addition, the sensitivity of the results to the discount rate, the total jump rate and the quadratic cost factor is investigated. The optimal results are most strongly sensitive to the rate of stochastic jumps and to the quadratic cost factor to a lesser extent when the deterministic bioeconomic parameters are taken from aggregate antarctic pelagic whaling data.Research supported in part by the National Science Foundation under grants MCS 81-01698 and MCS 83-00562.     

Dynamics of outgrowth in a continuum model of neurite elongation

Neurite outgrowth (dendrites and axons) should be a stable, but easily regulated process to enable a neuron to make its appropriate network connections during development. We explore the dynamics of outgrowth in a mathematical continuum model of neurite elongation. The model describes the construction of the internal microtubule cytoskeleton, which results from the production and transport of tubulin dimers and their assembly into microtubules at the growing neurite tip. Tubulin is assumed to be largely synthesised in the cell body from where it is transported by active mechanisms and by diffusion along the neurite. It is argued that this construction process is a fundamental limiting factor in neurite elongation. In the model, elongation is highly stable when tubulin transport is dominated by either active transport or diffusion, but oscillations in length may occur when both active transport and diffusion contribute. Autoregulation of tubulin production can eliminate these oscillations. In all cases a stable steady-state length is reached, provided there is intrinsic decay of tubulin. Small changes in growth parameters, such as the tubulin production rate, can lead to large changes in length. Thus cytoskeleton construction can be both stable and easily regulated, as seems necessary for neurite outgrowth during nervous system development. Action Editor: Upinder Bhalla     

Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) Methodology—Review

Frequency of model change and the vast amounts of time and cost required to make a changeover, also called time-based competition, has become a characteristic feature of modern manufacturing and new product development in automotive, aerospace, and other industries. This paper discusses the concept of time-based competition in manufacturing and design based on a review of on-going research related to stream-of-variation (SOVA or SoV) methodology. The SOVA methodology focuses on the development of modeling, analysis, and control of dimensional variation in complex multistage assembly processes (MAP) such as the automotive, aerospace, appliance, and electronics industries. The presented methodology can help in eliminating costly trial-and-error fine-tuning of new-product assembly processes attributable to unforeseen dimensional errors throughout the assembly process from design through ramp-up and production. Implemented during the product design phase, the method will produce math-based predictions of potential downstream assembly problems, based on evaluations of the design and a large array of process variables. By integrating product and process design in a pre-production simulation, SOVA can head off individual assembly errors that contribute to an accumulating set of dimensional variations, which ultimately result in out-of-tolerance parts and products. Once in the ramp-up stage of production, SOVA will be able to compare predicted misalignments with actual measurements to determine the degree of mismatch in the assemblies, diagnose the root causes of errors, isolate the sources from other assembly steps, and then, on the basis of the SOVA model and product measurements, recommend solutions.     

Monitoring change in aquatic invertebrate biodiversity: sample size, faunal elements and analytical methods

Replication is usually regarded as an integral part of biological sampling, yet the cost of extensive within-wetland replication prohibits its use in broad-scale monitoring of trends in aquatic invertebrate biodiversity. In this paper, we report results of testing an alternative protocol, whereby only two samples are collected from a wetland per monitoring event and then analysed using ordination to detect any changes in invertebrate biodiversity over time. Simulated data suggested ordination of combined data from the two samples would detect 20% species turnover and be a cost-effective method of monitoring changes in biodiversity, whereas power analyses showed about 10 samples were required to detect 20% change in species richness using ANOVA. Errors will be higher if years with extreme climatic events (e.g. drought), which often have dramatic short-term effects on invertebrate communities, are included in analyses. We also suggest that protocols for monitoring aquatic invertebrate biodiversity should include microinvertebrates. Almost half the species collected from the wetlands in this study were microinvertebrates and their biodiversity was poorly predicted by macroinvertebrate data.     

Localized Sampling Enables Monitoring of Cell State via Inline Electrospray Ionization Mass Spectrometry

Nascent advanced therapies, including regenerative medicine and cell and gene therapies, rely on the production of cells in bioreactors that are highly heterogeneous in both space and time. Unfortunately, advanced therapies have failed to reach a wide patient population due to unreliable manufacturing processes that result in batch variability and cost prohibitive production. This can be attributed largely to a void in existing process analytical technologies (PATs) capable of characterizing the secreted critical quality attribute (CQA) biomolecules that correlate with the final product quality. The Dynamic Sampling Platform (DSP) is a PAT for cell bioreactor monitoring that can be coupled to a suite of sensor techniques to provide real-time feedback on spatial and temporal CQA content in situ. In this study, DSP is coupled with electrospray ionization mass spectrometry and direct-from-culture sampling to obtain measures of CQA content in bulk media and the cell microenvironment throughout the entire cell culture process (≈3 weeks). Post hoc analysis of this real-time data reveals that sampling from the microenvironment enables cell state monitoring (e.g., confluence, differentiation). These results demonstrate that an effective PAT should incorporate both spatial and temporal resolution to serve as an effective input for feedback control in biomanufacturing.     

Self-assembly and type III protein export of the bacterial flagellum

The bacterial flagellum is a supramolecular structure consisting of a basal body, a hook and a filament. Most of the flagellar components are translocated across the cytoplasmic membrane by the flagellar type III protein export apparatus in the vicinity of the flagellar base, diffuse down the narrow channel through the nascent structure and self-assemble at its distal end with the help of a cap structure. Flagellar proteins synthesized in the cytoplasm are targeted to the export apparatus with the help of flagellum-specific chaperones and pushed into the channel by an ATPase, whose activity is controlled by its regulator to enable the energy of ATP hydrolysis to be efficiently coupled to the translocation reaction. The export apparatus switches its substrate specificity by monitoring the state of flagellar assembly in the cell exterior, allowing this huge and complex macromolecular assembly to be built efficiently by a highly ordered and well-regulated assembly process.     

Full Genome Virus Detection in Fecal Samples Using Sensitive Nucleic Acid Preparation,Deep Sequencing,and a Novel Iterative Sequence Classification Algorithm

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis.     

A fault identification and classification scheme for an automobile door assembly process

A process fault identification and classification scheme for an automobile door assembly process is presented based on multivariate in-line dimensional measurements and principal component factor analysis. First, the door assembly process and the dimensional measurement system are briefly introduced. Second, the technique of principal component factor analysis is presented for process fault identification. Process faults are summarized based on off-line identified case studies. Finally a machine classification scheme based on principal components and principal factors is presented and evaluated, using the pattern knowledge obtained off-line. This scheme is shown to be effective in classifying process faults using production data.     

Construction of hydrodynamic bead models from high-resolution X-ray crystallographic or nuclear magnetic resonance data.

Computer software such as HYDRO, based upon a comprehensive body of theoretical work, permits the hydrodynamic modeling of macromolecules in solution, which are represented to the computer interface as an assembly of spheres. The uniqueness of any satisfactory resultant model is optimized by incorporating into the modeling procedure the maximal possible number of criteria to which the bead model must conform. An algorithm (AtoB, for atoms to beads) that permits the direct construction of bead models from high resolution x-ray crystallographic or nuclear magnetic resonance data has now been formulated and tested. Models so generated then act as informed starting estimates for the subsequent iterative modeling procedure, thereby hastening the convergence to reasonable representations of solution conformation. Successful application of this algorithm to several proteins shows that predictions of hydrodynamic parameters, including those concerning solvation, can be confirmed.     

Improving Phrap-based assembly of the rat using "reliable" overlaps

The assembly methods used for whole-genome shotgun (WGS) data have a major impact on the quality of resulting draft genomes. We present a novel algorithm to generate a set of "reliable" overlaps based on identifying repeat k-mers. To demonstrate the benefits of using reliable overlaps, we have created a version of the Phrap assembly program that uses only overlaps from a specific list. We call this version PhrapUMD. Integrating PhrapUMD and our "reliable-overlap" algorithm with the Baylor College of Medicine assembler, Atlas, we assemble the BACs from the Rattus norvegicus genome project. Starting with the same data as the Nov. 2002 Atlas assembly, we compare our results and the Atlas assembly to the 4.3 Mb of rat sequence in the 21 BACs that have been finished. Our version of the draft assembly of the 21 BACs increases the coverage of finished sequence from 93.4% to 96.3%, while simultaneously reducing the base error rate from 4.5 to 1.1 errors per 10,000 bases. There are a number of ways of assessing the relative merits of assemblies when the finished sequence is available. If one views the overall quality of an assembly as proportional to the inverse of the product of the error rate and sequence missed, then the assembly presented here is seven times better. The UMD Overlapper with options for reliable overlaps is available from the authors at http://www.genome.umd.edu. We also provide the changes to the Phrap source code enabling it to use only the reliable overlaps.     

Barn swallows Hirundo rustica form eggs mainly from current food intake

Birds might form eggs from stored nutrients, from current food intake or from both. We examined whether stored nutrients were a substantial resource for egg production in an aerial insectivore, which had a variable food supply, but for which there was likely to be a cost for carrying additional mass. The mass changes of female barn swallows Hirundo rustica during the egg formation period were most simply explained by changes in the mass of the eggs and oviduct. Fat score and body mass excluding the eggs and oviduct did not vary systematically during egg formation. Egg production stopped altogether during particularly bad weather. The normal range in environmental conditions before and during laying had little influence on clutch size. Our results suggest that swallows form eggs primarily from current food intake, although our data do not exclude use of micronutrients from reserves.     

Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6–40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.     

A micromolar pool of antigenically distinct precursors is required to initiate cooperative assembly of hepatitis B virus capsids in Xenopus oocytes.

Assembly of hepatitis B virus capsid-like (core) particles occurs efficiently in a variety of heterologous systems via aggregation of approximately 180 molecules of a single 21.5-kDa core protein (p21.5), resulting in an icosahedral capsid structure with T = 3 symmetry. Recent studies on the assembly of hepatitis B virus core particles in Xenopus oocytes suggested that dimers of p21.5 represent the major building block from which capsids are generated. Here we determined the concentration dependence of this assembly process. By injecting serially diluted synthetic p21.5 mRNA into Xenopus oocytes, we expressed different levels of intracellular p21.5 and monitored the production of p21.5 dimers and capsids by radiolabeling and immunoprecipitation, by radioimmunoassay, or by quantitative enzyme-linked immunosorbent assay analysis. The data revealed that (i) p21.5 dimers and capsids are antigenically distinct, (ii) capsid assembly is a highly cooperative and concentration-dependent process, and (iii) p21.5 must accumulate to a signature concentration of approximately 0.7 to 0.8 microM before capsid assembly initiates. This assembly process is strikingly similar to the assembly of RNA bacteriophage R17 as defined by in vitro studies.     

Next-generation phylogenomics using a Target Restricted Assembly Method

Next-generation sequencing technologies are revolutionizing the field of phylogenetics by making available genome scale data for a fraction of the cost of traditional targeted sequencing. One challenge will be to make use of these genomic level data without necessarily resorting to full-scale genome assembly and annotation, which is often time and labor intensive. Here we describe a technique, the Target Restricted Assembly Method (TRAM), in which the typical process of genome assembly and annotation is in essence reversed. Protein sequences of phylogenetically useful genes from a species within the group of interest are used as targets in tblastn searches of a data set from a lane of Illumina reads for a related species. Resulting blast hits are then assembled locally into contigs and these contigs are then aligned against the reference “cDNA” sequence to remove portions of the sequences that include introns. We illustrate the Target Restricted Assembly Method using genomic scale datasets for 20 species of lice (Insecta: Psocodea) to produce a test phylogenetic data set of 10 nuclear protein coding gene sequences. Given the advantages of using DNA instead of RNA, this technique is very cost effective and feasible given current technologies.     

Metabolic costs of egg production in the European starling (Sturnus vulgaris)

The energy cost of egg production in passerine birds has typically been estimated to be 45%-60% of basal metabolic rate (BMR), but this is based on theoretical models using data on energy content of eggs and reproductive tissue; there are still very few empirical data on egg production costs. In this study, we directly measured resting metabolic rate (RMR) in egg-laying female European starlings (Sturnus vulgaris) over 3 yr. We compared these data with RMR of nonbreeding and chick-rearing birds and with estimated energy expenditure generated from a typical energy content model by using empirically derived data from body composition analysis for this species. We found marked variation in RMR between years and between reproductive stages, which complicates comparisons among breeding stages for the assessment of relative egg production costs. On the basis of this method, RMR during egg laying varied from +74% to -13% of nonbreeding RMR and from +20% to -7% of chick-rearing RMR. We therefore used an alternate approach: measuring changes in RMR through the complete cycle of follicle development and ovulation. The increase in RMR from the beginning of prelaying to the six-follicle stage (before first ovulation) when birds have a complete developing follicle hierarchy was 22.4%. This value is still much lower than that estimated from our energy content model. We discuss conceptual problems associated with the theoretical energy content approach but also suggest, on the basis of earlier work done in our lab, that the measured increase in RMR might still underestimate the actual cost of egg production if birds reallocate energy between different physiological systems.