La ségrégation du plasmide F d'Escherichia coli : régulation de l'activité ATPase de la protéine moteur de partition SopA

La ségrégation, ou partition, des chromosomes et des plasmides bactériens est l'étape fondamentale du cycle cellulaire qui assure la transmission de l'ensemble du génome aux cellules filles. C'est l'équivalent procaryote de la mitose. Des systèmes de ségrégation, appelés les loci par, ont été identifiés sur les plasmides à bas nombre de copies, et des homologues de ces systèmes de partition sont présents sur la majorité des chromosomes bactériens. Le système code deux protéines, une ATPase et une protéine qui se fixe spécifiquement sur une région centromérique. Ces deux protéines interagissent entre elles, permettent la localisation subcellulaire des réplicons et assurent ainsi leur maintien dans les générations futures. Au laboratoire, nous étudions l'un des systèmes modèles majeurs, le système de partition du plasmide F d'Escherichia coli, afin de déterminer le mécanisme moléculaire assurant le processus de ségrégation et son contrôle pendant le cycle cellulaire. La stabilité du plasmide F est assurée par le système de partition sopABC. Après la réplication du plasmide, la protéine SopB s'assemble sur le centromère sopC pour former un complexe de partition qui permet aux copies du plasmide d'être positionnés au centre de la cellule. Avant la division cellulaire les plasmides migrent aux positions 1/4 et 3/4 de la cellule et assurent ainsi l'héritage des réplicons dans les futures cellules filles. L'ATPase SopA est essentielle dans le processus de partition, mais son rôle n'est pas bien défini. SopA pourrait être impliquée dans les étapes de positionnement et/ou de déplacement des plasmides de part et d'autre de la cellule. SopA possède plusieurs activités. In vivo, SopA agit comme autorépresseur de l'opéron sopAB en se fixant sur la région promotrice. De plus elle interagit avec le complexe de partition et forme des polymères en présence d'ATP. Nous avons montré que cette activité est régulée par SopB et par l'ADN. L'activité ATPase de SopA est essentielle pour la partition. Elle est légèrement stimulée par SopB et par l'ADN, mais lorsque ces deux facteurs sont présents, elle est fortement stimulée. Nous avons entrepris de caractériser les interactions existantes entre ces trois protagonistes. Ainsi, nous avons démontré que cette stimulation nécessite une interaction de SopA avec SopB d'une part et avec l'ADN d'autre part. Nous avons également montré que le site centromérique sopC potentialise la stimulation de l'activité ATPase par l'intermédiaire de SopB. Nous nous sommes intéressés ensuite à l'interaction SopA-SopB, et nous avons mis en évidence que SopB stimule l'activité ATPase de SopA via un motif arginine finger. Pour finir, nous avons montré que in vivo, la stimulation de l'activité ATPase de SopA joue un rôle dans la régulation de l'opéron sopAB mais aussi dans la partition du plasmide F.Mitotic segregation of chromosomes and plasmids, termed partition in bacteria, is a fundamental step of the cell cycle that ensures the transmission of the whole genome to daughter cells. It is governed by specific genetic loci named par, first identified in low copy number plasmids and later found to be present as homologues in most bacterial chromosomes. Par loci encode two proteins, an ATPase and a DNA binding protein, and include a cis-acting centromeric site. These components interact with each other to direct the subcellular localization that ensures stability of their replicons. To determine the molecular mechanisms of the partition process and its control during the cell cycle, we study the Sop partition system of the Escherichia coli plasmid, F. Sop is one of the best-known partition systems. After F plasmid replication, SopB protein binds to the sopC centromeric site to form a partition complex. The complex on each plasmid copy interacts with SopA, an ATPase, and activates it to move the plasmid molecules towards the two cell poles. SopA ATPase is essential to the segregation process but its role is not defined. SopA has many activities. In vivo it represses its own operon by binding to the sopAB promoter. Moreover, in addition to its interaction with the partition complex it polymerizes in the presence of ATP. We have shown that SopB and DNA regulate this activity. Although the ATP-binding site on SopA is essential for partition, ATP hydrolysis by SopA is very weak. It is stimulated modestly by DNA and by SopB and strongly in the presence of both. We have characterized the interactions necessary for stimulation of ATP hydrolysis. First we found that the SopB-sopC partition complex is required for maximal stimulation. Then we showed that SopB and DNA contact SopA by two distinct interactions to fully activate ATPase activity. We also found that SopB activates SopA ATPase through an arginine finger motif. Finally, we have shown that in vivo, stimulation of the ATPase activity is necessary for both regulation of the sopAB operon and partition of plasmid F to be efficient

Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems

This paper introduces reviewability as a framework for improving the accountability of automated and algorithmic decision-making (ADM) involving machine learning. We draw on an understanding of ADM as a socio-technical process involving both human and technical elements, beginning before a decision is made and extending beyond the decision itself. While explanations and other model-centric mechanisms may assist some accountability concerns, they often provide insufficient information of these broader ADM processes for regulatory oversight and assessments of legal compliance. Reviewability involves breaking down the ADM process into technical and organisational elements to provide a systematic framework for determining the contextually appropriate record-keeping mechanisms to facilitate meaningful review - both of individual decisions and of the process as a whole. We argue that a reviewability framework, drawing on administrative law's approach to reviewing human decision-making, offers a practical way forward towards more a more holistic and legally-relevant form of accountability for ADM

Algorithmic Fairness in Mortgage Lending: from Absolute Conditions to Relational Trade-offs

AbstractTo address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in reality, the practical and ethical trade-offs are unavoidable and more complex. We introduce a new approach that considers fairness—not as a binary, absolute mathematical condition—but rather, as a relational notion in comparison to alternative decisionmaking processes. Using US mortgage lending as an example use case, we discuss the ethical foundations of each definition of fairness and demonstrate that our proposed methodology more closely captures the ethical trade-offs of the decision-maker, as well as forcing a more explicit representation of which values and objectives are prioritised.</jats:p

Algorithmic Fairness in Mortgage Lending: from Absolute Conditions to Relational Trade-offs

AbstractTo address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in reality, the practical and ethical trade-offs are unavoidable and more complex. We introduce a new approach that considers fairness—not as a binary, absolute mathematical condition—but rather, as a relational notion in comparison to alternative decisionmaking processes. Using US mortgage lending as an example use case, we discuss the ethical foundations of each definition of fairness and demonstrate that our proposed methodology more closely captures the ethical trade-offs of the decision-maker, as well as forcing a more explicit representation of which values and objectives are prioritised.</jats:p

Innovating with confidence: embedding AI governance and fairness in a financial services risk management framework

An increasing number of financial services (FS) companies are adopting solutions driven by artificial intelligence (AI) to gain operational efficiencies, derive strategic insights, and improve customer engagement. However, the rate of adoption has been low, in part due to the apprehension around its complexity and self-learning capability, which makes auditability a challenge in a highly regulated industry. There is limited literature on how FS companies can implement the governance and controls specific to AI-driven solutions. AI auditing cannot be performed in a vacuum; the risks are not confined to the algorithm itself, but rather permeates the entire organization. Using the risk of unfairness as an example, this paper will introduce the overarching governance strategy and control framework to address the practical challenges in mitigating risks AI introduces. With regulatory implications and industry use cases, this framework will enable leaders to innovate with confidence

Formalising trade-offs beyond algorithmic fairness: lessons from ethical philosophy and welfare economics

Abstract: There is growing concern that decision-making informed by machine learning (ML) algorithms may unfairly discriminate based on personal demographic attributes, such as race and gender. Scholars have responded by introducing numerous mathematical definitions of fairness to test the algorithm, many of which are in conflict with one another. However, these reductionist representations of fairness often bear little resemblance to real-life fairness considerations, which in practice are highly contextual. Moreover, fairness metrics tend to be implemented within narrow and targeted fairness toolkits for algorithm assessments that are difficult to integrate into an algorithm’s broader ethical assessment. In this paper, we derive lessons from ethical philosophy and welfare economics as they relate to the contextual factors relevant for fairness. In particular we highlight the debate around the acceptability of particular inequalities and the inextricable links between fairness, welfare and autonomy. We propose Key Ethics Indicators (KEIs) as a way towards providing a more holistic understanding of whether or not an algorithm is aligned to the decision-maker’s ethical values

Entrapment neuropathy results in different microRNA expression patterns from denervation injury in rats

<p>Abstract</p> <p>Background</p> <p>To compare the microRNA (miRNA) expression profiles in neurons and innervated muscles after sciatic nerve entrapment using a non-constrictive silastic tube, subsequent surgical decompression, and denervation injury.</p> <p>Methods</p> <p>The experimental L4-L6 spinal segments, dorsal root ganglia (DRGs), and soleus muscles from each experimental group (sham control, denervation, entrapment, and decompression) were analyzed using an Agilent rat miRNA array to detect dysregulated miRNAs. In addition, muscle-specific miRNAs (miR-1, -133a, and -206) and selectively upregulated miRNAs were subsequently quantified using real-time reverse transcription-polymerase chain reaction (real-time RT-PCR).</p> <p>Results</p> <p>In the soleus muscles, 37 of the 47 miRNAs (13.4% of the 350 unique miRNAs tested) that were significantly downregulated after 6 months of entrapment neuropathy were also among the 40 miRNAs (11.4% of the 350 unique miRNAs tested) that were downregulated after 3 months of decompression. No miRNA was upregulated in both groups. In contrast, only 3 miRNAs were upregulated and 3 miRNAs were downregulated in the denervated muscle after 6 months. In the DRGs, 6 miRNAs in the entrapment group (miR-9, miR-320, miR-324-3p, miR-672, miR-466b, and miR-144) and 3 miRNAs in the decompression group (miR-9, miR-320, and miR-324-3p) were significantly downregulated. No miRNA was upregulated in both groups. We detected 1 downregulated miRNA (miR-144) and 1 upregulated miRNA (miR-21) after sciatic nerve denervation. We were able to separate the muscle or DRG samples into denervation or entrapment neuropathy by performing unsupervised hierarchal clustering analysis. Regarding the muscle-specific miRNAs, real-time RT-PCR analysis revealed an ~50% decrease in miR-1 and miR-133a expression levels at 3 and 6 months after entrapment, whereas miR-1 and miR-133a levels were unchanged and were decreased after decompression at 1 and 3 months. In contrast, there were no statistical differences in the expression of miR-206 during nerve entrapment and after decompression. The expression of muscle-specific miRNAs in entrapment neuropathy is different from our previous observations in sciatic nerve denervation injury.</p> <p>Conclusions</p> <p>This study revealed the different involvement of miRNAs in neurons and innervated muscles after entrapment neuropathy and denervation injury, and implied that epigenetic regulation is different in these two conditions.</p

Canalization and developmental stability in the Brachyrrhine mouse

The semi-dominant Br mutation affects presphenoid growth, producing the facial retrognathism and globular neurocranial vault that characterize heterozygotes. We analysed the impact of this mutation on skull shape, comparing heterozygotes to wildtype mice, to determine if the effects are skull-wide or confined to the sphenoid region targeted by the mutation. In addition, we examined patterns of variability of shape for the skull as a whole and for three regions (basicranium, face and neurocranium). We found that the Br mice differed significantly from wildtype mice in skull shape in all three regions as well as in the shape of the skull as a whole. However, the significant increases in variance and fluctuating asymmetry were found only in the basicranium of mutant mice. These results suggest that the mutation has a significant effect on the underlying developmental architecture of the skull, which produces an increase in phenotypic variability that is localized to the anatomical region in which the mean phenotype is most dramatically affected. These results suggest that the same developmental mechanisms that produce the change in phenotypic mean also produce the change in variance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75710/1/j.1469-7580.2006.00527.x.pd