Multiplexing rhythmic information by spike timing dependent plasticity

by Nimrod Sherf, Shamir Maoz

Rhythmic activity has been associated with a wide range of cognitive processes including the encoding of sensory information, navigation, the transfer of information and others. Rhythmic activity in the brain has also been suggested to be used for multiplexing information. Multiplexing is the ability to transmit more than one signal via the same channel. Here we focus on frequency division multiplexing, in which different signals are transmitted in different frequency bands. Recent work showed that spike-timing-dependent plasticity (STDP) can facilitate the transfer of rhythmic activity downstream the information processing pathway. However, STDP has also been known to generate strong winner-take-all like competition between subgroups of correlated synaptic inputs. This competition between different rhythmicity channels, induced by STDP, may prevent the multiplexing of information. Thus, raising doubts whether STDP is consistent with the idea of multiplexing. This study explores whether STDP can facilitate the multiplexing of information across multiple frequency channels, and if so, under what conditions. We address this question in a modelling study, investigating the STDP dynamics of two populations synapsing downstream onto the same neuron in a feed-forward manner. Each population was assumed to exhibit rhythmic activity, albeit in a different frequency band. Our theory reveals that the winner-take-all like competitions between the two populations is limited, in the sense that different rhythmic populations will not necessarily fully suppress each other. Furthermore, we found that for a wide range of parameters, the network converged to a solution in which the downstream neuron responded to both rhythms. Yet, the synaptic weights themselves did not converge to a fixed point, rather remained dynamic. These findings imply that STDP can support the multiplexing of rhythmic information, and demonstrate how functionality (multiplexing of information) can be retained in the face of continuous remodeling of all the synaptic weights. The constraints on the types of STDP rules that can support multiplexing provide a natural test for our theory.

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Stochastic ordering of complexoform protein assembly by genetic circuits

by Mikkel Herholdt Jensen, Eliza J. Morris, Hai Tran, Michael A. Nash, Cheemeng Tan

Top-down proteomics has enabled the elucidation of heterogeneous protein complexes with different cofactors, post-translational modifications, and protein membership. This heterogeneity is believed to play a previously unknown role in cellular processes. The different molecular forms of a protein complex have come to be called “complex isoform” or “complexoform”. Despite the elucidation of the complexoform, it remains unclear how and whether cellular circuits control the distribution of a complexoform. To help address this issue, we first simulate a generic three-protein complexoform to reveal the control of its distribution by the timing of gene transcription, mRNA translation, and protein transport. Overall, we ran 265 computational experiments: each averaged over 1,000 stochastic simulations. Based on the experiments, we show that genes arranged in a single operon, a cascade, or as two operons all give rise to the different protein composition of complexoform because of timing differences in protein-synthesis order. We also show that changes in the kinetics of expression, protein transport, or protein binding dramatically alter the distribution of the complexoform. Furthermore, both stochastic and transient kinetics control the assembly of the complexoform when the expression and assembly occur concurrently. We test our model against the biological cellulosome system. With biologically relevant rates, we find that the genetic circuitry controls the average final complexoform assembly and the variation in the assembly structure. Our results highlight the importance of both the genetic circuit architecture and kinetics in determining the distribution of a complexoform. Our work has a broad impact on our understanding of non-equilibrium processes in both living and synthetic biological systems.

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It’s about time: Analysing simplifying assumptions for modelling multi-step pathways in systems biology

by Niklas Korsbo, Henrik Jönsson

Thoughtful use of simplifying assumptions is crucial to make systems biology models tractable while still representative of the underlying biology. A useful simplification can elucidate the core dynamics of a system. A poorly chosen assumption can, however, either render a model too complicated for making conclusions or it can prevent an otherwise accurate model from describing experimentally observed dynamics. Here, we perform a computational investigation of sequential multi-step pathway models that contain fewer pathway steps than the system they are designed to emulate. We demonstrate when such models will fail to reproduce data and how detrimental truncation of a pathway leads to detectable signatures in model dynamics and its optimised parameters. An alternative assumption is suggested for simplifying such pathways. Rather than assuming a truncated number of pathway steps, we propose to use the assumption that the rates of information propagation along the pathway is homogeneous and, instead, letting the length of the pathway be a free parameter. We first focus on linear pathways that are sequential and have first-order kinetics, and we show how this assumption results in a three-parameter model that consistently outperforms its truncated rival and a delay differential equation alternative in recapitulating observed dynamics. We then show how the proposed assumption allows for similarly terse and effective models of non-linear pathways. Our results provide a foundation for well-informed decision making during model simplifications.

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Different states of priority recruit different neural representations in visual working memory

by Qing Yu, Chunyue Teng, Bradley R. Postle

We used functional magnetic resonance imaging (fMRI) to investigate the neural codes for representing stimulus information held in different states of priority in working memory. Human participants (male and female) performed delayed recall for 2 oriented gratings that could appear in any of several locations. Priority status was manipulated by a retrocue, such that one became the prioritized memory item (PMI) and another the unprioritized memory item (UMI). Using inverted encoding models (IEMs), we found that, in early visual cortex, the orientation of the UMI was represented in a neural representation that was rotated relative to the PMI. In intraparietal sulcus (IPS), we observed the analogous effect for the representation of the location of the UMI. Taken together, these results provide evidence for a common remapping mechanism that may be responsible for representing stimulus identity and stimulus context with different levels of priority in working memory.

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All three mammalian MutL complexes are required for repeat expansion in a mouse cell model of the Fragile X-related disorders

by Carson J. Miller, Geum-Yi Kim, Xiaonan Zhao, Karen Usdin

Expansion of a CGG-repeat tract in the 5’ untranslated region of the FMR1 gene causes the fragile X-related disorders (FXDs; aka the FMR1 disorders). The expansion mechanism is likely shared by the 35+ other diseases resulting from expansion of a disease-specific microsatellite, but many steps in this process are unknown. We have shown previously that expansion is dependent upon functional mismatch repair proteins, including an absolute requirement for MutLγ, one of the three MutL heterodimeric complexes found in mammalian cells. We demonstrate here that both MutLα and MutLβ, the two other MutL complexes present in mammalian cells, are also required for most, if not all, expansions in a mouse embryonic stem cell model of the FXDs. A role for MutLα and MutLβ is consistent with human GWA studies implicating these complexes as modifiers of expansion risk in other Repeat Expansion Diseases. The requirement for all three complexes suggests a novel model in which these complexes co-operate to generate expansions. It also suggests that the PMS1 subunit of MutLβ may be a reasonable therapeutic target in those diseases in which somatic expansion is an important disease modifier.

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c-di-GMP inhibits LonA-dependent proteolysis of TfoY in Vibrio cholerae

by Avatar Joshi, Samar A. Mahmoud, Soo-Kyoung Kim, Justyne L. Ogdahl, Vincent T. Lee, Peter Chien, Fitnat H. Yildiz

The LonA (or Lon) protease is a central post-translational regulator in diverse bacterial species. In Vibrio cholerae, LonA regulates a broad range of behaviors including cell division, biofilm formation, flagellar motility, c-di-GMP levels, the type VI secretion system (T6SS), virulence gene expression, and host colonization. Despite LonA’s role in cellular processes critical for V. cholerae’s aquatic and infectious life cycles, relatively few LonA substrates have been identified. LonA protease substrates were therefore identified through comparison of the proteomes of wild-type and ΔlonA strains following translational inhibition. The most significantly enriched LonA-dependent protein was TfoY, a known regulator of motility and the T6SS in V. cholerae. Experiments showed that TfoY was required for LonA-mediated repression of motility and T6SS-dependent killing. In addition, TfoY was stabilized under high c-di-GMP conditions and biochemical analysis determined direct binding of c-di-GMP to LonA results in inhibition of its protease activity. The work presented here adds to the list of LonA substrates, identifies LonA as a c-di-GMP receptor, demonstrates that c-di-GMP regulates LonA activity and TfoY protein stability, and helps elucidate the mechanisms by which LonA controls important V. cholerae behaviors.

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The genome polishing tool POLCA makes fast and accurate corrections in genome assemblies

by Aleksey V. Zimin, Steven L. Salzberg

The introduction of third-generation DNA sequencing technologies in recent years has allowed scientists to generate dramatically longer sequence reads, which when used in whole-genome sequencing projects have yielded better repeat resolution and far more contiguous genome assemblies. While the promise of better contiguity has held true, the relatively high error rate of long reads, averaging 8–15%, has made it challenging to generate a highly accurate final sequence. Current long-read sequencing technologies display a tendency toward systematic errors, in particular in homopolymer regions, which present additional challenges. A cost-effective strategy to generate highly contiguous assemblies with a very low overall error rate is to combine long reads with low-cost short-read data, which currently have an error rate below 0.5%. This hybrid strategy can be pursued either by incorporating the short-read data into the early phase of assembly, during the read correction step, or by using short reads to “polish” the consensus built from long reads. In this report, we present the assembly polishing tool POLCA (POLishing by Calling Alternatives) and compare its performance with two other popular polishing programs, Pilon and Racon. We show that on simulated data POLCA is more accurate than Pilon, and comparable in accuracy to Racon. On real data, all three programs show similar performance, but POLCA is consistently much faster than either of the other polishing programs.

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