работа «Биологические компьютеры» (стр. 9 из 9)

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In the next step, we performed evaluation experiments for full DNF and CNF expressions. The connection of the siRNAs and their targets to endogenous input variables is shown in Supplementary Table 2 online. We constructed circuits to evaluate two expressions in DNF form, D1: (A AND B AND C) OR (D AND E) and D2: (A AND C AND E) OR (NOT(A) AND B). The same siRNA (FF3) was

used differently in D1 and D2, once as a variable E and once as a negated variable NOT(A). As a result, siRNAs T1 and FF3 were never applied together during D2 evaluation. We then tested all possible truth-value assignments for the variables in each expression: 32 for the D1 and 16 for D2 (Table 1a). The distribution of output levels in both expressions is shown in Supplementary Figure 4 online. It demonstrates a clear separation between the groups of False and True outputs as required from a Boolean evaluator, with an average 16-fold difference between output levels in False and True groups. The evaluation of the D1 expression, with all variables being True and no siRNAs present, resulted in more than twice the output of others owing to the parallel production of the output from both clause mRNAs. This high value is also interpreted as True10, 12. In the expression D2, we obtained one imperfect False evaluation (A:T, B:F, C:F, E:T) that generated 0.32 expression units relative to the lowest unsuppressed ('True') output level. This cannot be explained solely by the incomplete downregulation of the clause molecule Target-(E)-(A)-(C) by SI4, as the same siRNA worked about two to three times more efficiently when the clause molecule was tested alone (e.g., see Supplementary Fig. 3 online). However, increasing the amount of the SI4 siRNA from 2.5 pmol to 10 pmol per transfection resulted in a repression improvement down to 0.08 units (data not shown). Similar improvement was obtained with the (A:F, B:F, C:T, E:T) evaluation that generates 0.22 units under standard conditions but may be reduced fourfold by an increase in the T1 siRNA level.

Table 1: Operation of the Boolean evaluator

Full table

We next fused siRNA targets to the 3'-UTR of the LacI repressor27 driven by the cytomegalovirus (CMV) promoter (Fig. 1d) to evaluate a single-clause CNF

expression C1: (D OR E) and a two-clause, two-variable expression C2: (D) AND (E). In the latter expression, each single-variable clause molecule was modified by the triple tandem repeat of the target instead of a single occurrence to improve repression efficiency28. The dsRed-monomer reporter of the truth values in CNF evaluators was under the control of the CAGOP promoter27 (Fig. 2d). The CNF evaluator (Table 1b) performs an AND operation between clauses and an OR operation within a clause; however, currently the CNF evaluator is quantitatively less robust than its DNF counterpart. We expect that tight repression on the one hand, and efficient downregulation by the siRNA on the other, will improve its performance. Apart from increasing the strength of the operator (CAGOP versus CMV-LacO) and fusing tandem repeats, we also tested a stronger repressor LacI-KRAB and thus were able to double the performance of the C1 evaluator (Table 1b). Nonetheless, additional fine-tuning of both the operator and the targets is still needed to improve scalability.

Our design framework allows parallel evaluation of an expression and its negation; this can improve the overall performance of the system. When two anticorrelated outputs are produced in parallel, their difference is a better indicator of the process outcome than individual outputs2. For example, a DNF expression e generates an evaluator circuit and a sensory interface that correspond to this expression; the result is judged by output O1. We can construct a parallel circuit where the output O1 is replaced by a repressor that regulates an expression of a different output O2. It is easy to see that when both circuits use the same sensory interface, the output O2 reflects the truth value of the expression NOT(e) and therefore the outputs O1 and O2 are anticorrelated. Table 1c demonstrates this feature for the trivial single-literal expression E1: (D).

This report represents a step toward in vivo programmable decision-making molecular automata by implementation of a computing core that evaluates logic expressions in standard forms. These forms, evaluated using two-level logic circuits, may entail an exponential increase in size for representing certain logic functions relative to multilevel circuits12. However, a reduction in the number of

computation stages reduces the overall processing time of the circuit. Noise and signal degradation are an issue in both circuit architectures; signal restoration, that is, improving the ON/OFF ratio at intermediate stages greatly improves scalability and performance. In the case where the two-level logic representation cannot be implemented efficiently owing to the accumulation of incompletely repressed clauses, it is also possible to subdivide the computation into a hierarchy and introduce signal restoration. Currently the performance of our circuits is comparable to similar in vitro and in vivo logic networks that do not use this restoration. Certain mammalian transcriptional logic gates achieve a 20-fold average difference between the molecular levels that correspond to True and False outputs in 2–3 input logic gates10, and an evolutionarily optimized single-input cascade29 enables about a sevenfold difference between these outputs. In vitro and in vivo riboswitch systems1, 4, 5, 13, 16 and a FokI-based protein-release system14 achieve 10- to 100-fold True to False ratios. Large-scale in vitro systems1, 2, 3 show 10-fold True:False ratio. An order-of-magnitude difference in our experiments may be enough for many applications. However, we expect that signal-restoration motifs will improve performance, as suggested by a >1,000-fold On:Off ratio in a transcriptional circuit30 and a >100-fold True:False ratio in an in vitro system12.

We propose a sensory mechanism whereby one siRNA mediates the presence, and another the absence, of a given input through direct and opposite regulatory links, with the latter implementing the logic NOT operation12 (Supplementary Fig. 5 online). We envision both activation and inactivation mechanisms of siRNA-like molecules by diverse molecular inputs, as required by the automaton architecture. For example, recent work6 has demonstrated both inhibition and activation of siRNA by a small molecule whereas a DNA automaton2 used distinct subsequences of an mRNA molecule to oppositely regulate two different siRNA-like double-stranded DNA structures. An alternative mechanism would involve only one kind of regulatory link between the input and one of the mediators, with an additional inhibitory interaction between this and the

complementary mediator (Supplementary Fig. 5). Our approach seems preferable for two reasons. First, in our arrangement, we require two molecular interactions for an input that is tested for either presence or absence, and four interactions when an input is tested for both (that is, appears both as a positive and a negative literal in a logic expression). In the alternative, an input tested for its absence requires three interactions (Supplementary Fig. 5), increasing the total number of interactions per circuit. Second, our design requires at most two consecutive interactions upstream of the computing core, whereas the alternative requires three when we test for an input absence; an increased number of steps will increase the probability of a failure.

Implementation of our circuits is challenging as it requires multiple and efficient siRNA structures with minimal crosstalk. We have largely overcome these challenges by using siRNA molecules developed with the help of computer-aided design15. In the future, the utility of such design principles for the construction of automata could be further improved by taking into account the selectivity and efficiency of siRNA-mediators both as sensors and as regulators of gene expression. Ultimately, molecular computing and synthetic biology may create molecular information-processing networks that are better than natural ones in their quantitative performance while permitting novel functionalities.

Приложение Г

БИОГРАФИЯ МИСТЕРА СЕЙМОРА КРЭЯ

Сеймор Р.Крей в 1950 году получил степень бакалавра наук електроинженерии в Университете Миннесоты. В 1951 он закончил магистратуру по специальности прикладной математики в этом же Университете.

С 1950 по 1951 годы Крей занимал несколько разных должностей в Ассоциации Инженерных Исследований (ERA), Сент-Пол, Миннесота. В ERA он работал над усовершенствованием ERA 1101 научного компьютера для правительства США. Позже он разработал большую часть ERA 1103, первого коммерчески успешного научного компьютера. В это время он также работал над множеством других компьютерных технологий, от вакуумных труб и магнитных усилителей до транзисторов.

Мистер Крей начинал свою карьеру как разработчик высококлассного компьютерного оборудования. Он был одним из основателей Корпорации контроля информации (CDC) в 1957 году и занимался разработкой самых успешных компьютеров этой компании, систем CDC 1604, 6600 и 7600. Он был директором CDC с 1957 по 1965 годы и занимал должность старшего вице-президента к моменту своего ухода в 1972 году.

В 1972 году Крей основал Cray Research, Inc. для разработки и создания самых совершенных суперкомпьютеров широкого пользования. Его компьютер CRAY-1 открыл новый стандарт во сверхвысокопроизводительных вычислениях на момент своего выпуска в 1976 году, а компьютерная система CRAY-2 представленная в 1985 году продвинула программирование для суперкомпьютеров далеко вперед.

В июле 1989 года он основал Компьютерную Корпорацию Крея для продолжения расширения рамок научного и инженерного программирования. Он смог сопоставить галлий арсенид логическое

программирование и микроминиатюрные суперкомпьютеры. CRAY-4 достиг тактовую чистоту в одну наносекунду.

Крей автор множества технологий, которые были запатентированы компаниями, в которых он работал. Среди наиболее значимых: технология векторного регистра CRAY-1, технологии охлаждения для компьютеров серии CRAY, CDC 6600 фреон-охлаждающая система, магнитный усилитель для ERA, трехмерная взаимосвязанная модульная конструкция, использованная для CRAY-3 и для CRAY-5, и галлий арсенид логическое программирование.