Biology subjects

Maurer, D.

Publications and source records attributed to Maurer, D..

5 recordsLinked to original sources

bioRxiv2026

The bacterial iron sensor IdeR distinguishes DNA sequences by applying stress to non-cognate DNA

The transcription factor IdeR regulates iron homeostasis in many gram-positive bacteria. It primarily functions as a repressor of iron uptake genes by binding to their promoters and blocking RNA polymerase access. IdeR recognizes a highly conserved DNA sequence consisting of four palindromic 5'-C1C2T3A4A5 repeats. For target site recognition, IdeR requires a thymine in position 3 of the repeat and at least one cytosine in the first two positions, while the identity of the bases in positions 4 and 5 is less important. We have previously shown that IdeR recognizes its target sequences through indirect or shape readout, rather than direct interactions with the bases. However, the mechanism of indirect recognition is unknown. Here we employed molecular dynamics simulations, X-ray crystallography, and DNA-binding assays to investigate the thermodynamic principles underlying accurate pyrimidine recognition by IdeR. We found that the recognition helix of IdeR forms a differential dielectric cleft that accommodates the C-H edge of the 5'-C1C2T3 sequence, with a polar pocket for the first two bases and a non-polar pocket for the third. The local dielectric environment of IdeR applies strain to non-cognate DNA, leading to non-productive binding and thereby ensuring the fidelity of target DNA reading.

biochemistry↗

bioRxiv2024

Impact of a transient neonatal visual deprivation on the development of the ventral occipito-temporal cortex in humans

How does experience shape the development of visual brain regions? We demonstrate that a transient period of visual deprivation early in life in humans leads to permanent alteration in the function of the early visual cortex (EVC), while leaving the categorical coding of downstream ventral occipito-temporal cortex (VOTC) mostly unaffected. We used fMRI to characterize the brain response to five categories (faces, bodies, objects, buildings and words) in a rare group of cataract-reversal individuals who experienced a transient period of blindness early in life, and in matched participants with typical visual development. We show that the encoding of low-level visual properties is impaired in EVC in cataract-reversal participants, while the categorical response in the VOTC is preserved. When altering the visual properties of our stimuli to mimic in controls the deficit of EVC response of the cataract, we observe a cascading alteration of the categorical coding from EVC to VOTC that is not observed in the cataract-reversal group. Our results show that a typical visual categorical organization develops in VOTC despite a period of visual deprivation early in life and in the presence of impaired processing in EVC. A deep neural network exposed to a visual diet that emulates the experience of our participants reproduced our brain observations within an artificial system. These findings emphasize how specific visual regions are differently affected by a period of visual deprivation early in life, with information encoded in EVC being permanently affected, while the categorical coding in VOTC shows resilience to deprivation.

neuroscience↗

bioRxiv2024

Modeling reveals the strength of weak interactions in stacked ring assembly

Cells employ many large macromolecular machines for the execution and regulation of processes that are vital for cell and organismal viability. Interestingly, cells cannot synthesize these machines as functioning units. Instead, cells synthesize the molecular parts that must then assemble into the functional complex. Many important machines, including chaperones like GroEL and proteases like the proteasome, are comprised protein rings that are stacked on top of one another. While there is some experimental data regarding how stacked-ring complexes like the proteasome self-assemble, a comprehensive understanding of the dynamics of stacked ring assembly is currently lacking. Here, we developed a mathematical model of stacked trimer assembly, and performed an analysis of the assembly of the stacked homomeric trimer, which is the simplest stacked ring architecture. We found that stacked rings are particularly susceptible to a form of kinetic trapping that we term "deadlock," in which the system gets stuck in a state where there are many large intermediates that are not the fully-assembled structure, but that cannot productively react. When interaction affinities are uniformly strong, deadlock severely limits assembly yield. We thus predicted that stacked rings would avoid situations where all interfaces in the structure have high affinity. Analysis of available crystal structures indicated that indeed the majority - if not all - of stacked trimers do not contain uniformly strong interactions. Finally, to better understand the origins of deadlock, we developed a formal pathway analysis and showed that, when all the binding affinities are strong, many of the possible pathways are utilized. In contrast, optimal assembly strategies utilize only a small number of patwhays. Our work suggests that deadlock is a critical factor influencing the evolution of macromolecular machines, and provides general principles for not only understanding existing machines but also for the design of novel structures that can self-assemble efficiently. Statement of SignificanceUnderstanding the assembly macromolecular machines is important for understanding a wide range of cellular processes. Here, we use mathematical models to study the assembly of stacked rings, which are a common motif in these machines. Our models revealed that these complexes can readily get "stuck" during assembly when the binding affinity between subunits is too strong. This suggests an evolutionary pressure to favor weaker interactions, and our analysis of solved structures confirmed this prediction. Our findings not only contribute to the fundamental understanding of assembly but also offer insights into the evolutionary pressures shaping the architecture of stacked rings, and have implications for both cell and synthetic biology.

biophysics↗

bioRxiv2021

The bacterial iron sensor IdeR recognizes its DNA targets by indirect readout

IdeR is the main transcriptional regulator controlling iron homeostasis genes in Actinobacteria, including species from the Corynebacterium, Mycobacterium, and Streptomyces genera, as well as the erythromycin-producing bacterium Saccharopolyspora erythraea. Despite being a well-studied transcription factor since the identification of the Diphtheria toxin repressor DtxR three decades ago, the details of how IdeR proteins recognize their highly conserved 19-bp DNA target remain to be elucidated. The results of our structural and mutational studies support a model wherein IdeR uses an indirect readout mechanism, identifying its targets via the sequence-specific DNA backbone structure rather than through direct contacts with the DNA bases. Furthermore, we show that IdeR efficiently recognizes a shorter palindromic sequence corresponding to a half binding site as compared to the full 19-bp target previously reported, expanding the number of potential target genes controlled by IdeR proteins.

biochemistry↗

bioRxiv2017

Weak interactions between groups and physical drivers of community dynamics in coastal phytoplankton

Phytoplanktonic communities maintain a high diversity in a seemingly homogeneous environment, competing for the same set of resources. Many theories have been proposed to explain this coexistence despite likely competition, such as contrasted responses to temporal environmental variation. However, theory has developed at a faster pace than its empirical evaluation using field data, that requires to infer biotic and abiotic drivers of community dynamics from observational time series. Here, we combine autoregressive models with a data set spanning more than 20 years of biweekly plankton counts and abiotic variables, including nutrients and physical variables. By comparing models dominated by nutrients or physical variables (hydrodynamics and climate), we first explore which abiotic factors contribute more to phytoplankton growth and decline. We find that physical drivers - such as irradiance, wind, and salinity - explain some of the variability in abundances unexplained by biotic interactions. In contrast, responses to nutrients explain less of phytoplankton variability. Concerning biotic drivers of community dynamics, multivariate autoregressive models reveal that competition between different groups (at the genus level for most) has a much weaker effect on population growth rates than competition within a group. In fact, the few biotic interactions between genera that are detected are frequently positive. Hence, our system is unlikely to be best represented as a set of competitors whose differing responses to fluctuating environments allow coexistence, as in \"paradox of the plankton\" models with a storage effect or a relative nonlinearity of competition. Coexistence is more likely to result from stabilizing niche differences, manifested through high intragroup density-dependence. Competition between planktonic groups and nutrients are often invoked as drivers of phytoplankton dynamics; our findings suggest instead that more attention should be given to the physical structure of the environment and natural enemies, for coastal phytoplankton at least.

ecology↗